Upload folder using huggingface_hub
Browse filesThis view is limited to 50 files because it contains too many changes.
See raw diff
- .gitattributes +10 -0
- .gitignore +40 -0
- README.md +112 -3
- aaai/aaai2021.json +0 -0
- aaai/aaai2022.json +0 -0
- aaai/aaai2023.json +0 -0
- aaai/aaai2024.json +3 -0
- aaai/aaai2025.json +3 -0
- acl/acl2021.json +0 -0
- acl/acl2022.json +0 -0
- acl/acl2023.json +0 -0
- acl/acl2024.json +0 -0
- acmmm/acmmm2024.json +0 -0
- aistats/aistats2025.json +0 -0
- colm/colm2024.json +0 -0
- corl/corl2021.json +0 -0
- corl/corl2022.json +0 -0
- corl/corl2023.json +0 -0
- corl/corl2024.json +0 -0
- cvpr/cvpr2013.json +0 -0
- cvpr/cvpr2014.json +0 -0
- cvpr/cvpr2015.json +0 -0
- cvpr/cvpr2016.json +0 -0
- cvpr/cvpr2017.json +0 -0
- cvpr/cvpr2018.json +0 -0
- cvpr/cvpr2019.json +0 -0
- cvpr/cvpr2020.json +0 -0
- cvpr/cvpr2021.json +0 -0
- cvpr/cvpr2022.json +0 -0
- cvpr/cvpr2023.json +0 -0
- cvpr/cvpr2024.json +0 -0
- cvpr/cvpr2025.json +0 -0
- eccv/eccv2018.json +0 -0
- eccv/eccv2020.json +0 -0
- eccv/eccv2022.json +0 -0
- eccv/eccv2024.json +0 -0
- emnlp/emnlp2021.json +0 -0
- emnlp/emnlp2022.json +0 -0
- emnlp/emnlp2023.json +0 -0
- emnlp/emnlp2024.json +0 -0
- iccv/iccv2013.json +0 -0
- iccv/iccv2015.json +0 -0
- iccv/iccv2017.json +0 -0
- iccv/iccv2019.json +0 -0
- iccv/iccv2021.json +0 -0
- iccv/iccv2023.json +0 -0
- iclr/iclr2013.json +1141 -0
- iclr/iclr2014.json +1175 -0
- iclr/iclr2017.json +0 -0
- iclr/iclr2018.json +0 -0
.gitattributes
CHANGED
|
@@ -57,3 +57,13 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
|
|
| 57 |
# Video files - compressed
|
| 58 |
*.mp4 filter=lfs diff=lfs merge=lfs -text
|
| 59 |
*.webm filter=lfs diff=lfs merge=lfs -text
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 57 |
# Video files - compressed
|
| 58 |
*.mp4 filter=lfs diff=lfs merge=lfs -text
|
| 59 |
*.webm filter=lfs diff=lfs merge=lfs -text
|
| 60 |
+
aaai/aaai2024.json filter=lfs diff=lfs merge=lfs -text
|
| 61 |
+
aaai/aaai2025.json filter=lfs diff=lfs merge=lfs -text
|
| 62 |
+
iclr/iclr2022.json filter=lfs diff=lfs merge=lfs -text
|
| 63 |
+
iclr/iclr2023.json filter=lfs diff=lfs merge=lfs -text
|
| 64 |
+
iclr/iclr2024.json filter=lfs diff=lfs merge=lfs -text
|
| 65 |
+
iclr/iclr2025.json filter=lfs diff=lfs merge=lfs -text
|
| 66 |
+
nips/nips2021.json filter=lfs diff=lfs merge=lfs -text
|
| 67 |
+
nips/nips2022.json filter=lfs diff=lfs merge=lfs -text
|
| 68 |
+
nips/nips2023.json filter=lfs diff=lfs merge=lfs -text
|
| 69 |
+
nips/nips2024.json filter=lfs diff=lfs merge=lfs -text
|
.gitignore
ADDED
|
@@ -0,0 +1,40 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
# Python
|
| 2 |
+
.history
|
| 3 |
+
__pycache__/
|
| 4 |
+
*.py[cod]
|
| 5 |
+
*$py.class
|
| 6 |
+
*.so
|
| 7 |
+
.Python
|
| 8 |
+
env/
|
| 9 |
+
build/
|
| 10 |
+
develop-eggs/
|
| 11 |
+
dist/
|
| 12 |
+
downloads/
|
| 13 |
+
eggs/
|
| 14 |
+
.eggs/
|
| 15 |
+
lib/
|
| 16 |
+
lib64/
|
| 17 |
+
parts/
|
| 18 |
+
sdist/
|
| 19 |
+
var/
|
| 20 |
+
*.egg-info/
|
| 21 |
+
.installed.cfg
|
| 22 |
+
*.egg
|
| 23 |
+
|
| 24 |
+
# Streamlit
|
| 25 |
+
.streamlit/
|
| 26 |
+
|
| 27 |
+
# IDE
|
| 28 |
+
.idea/
|
| 29 |
+
.vscode/
|
| 30 |
+
*.swp
|
| 31 |
+
*.swo
|
| 32 |
+
|
| 33 |
+
# Operating System
|
| 34 |
+
.DS_Store
|
| 35 |
+
Thumbs.db
|
| 36 |
+
|
| 37 |
+
# Generated files
|
| 38 |
+
filtered_results-*.json
|
| 39 |
+
|
| 40 |
+
*.csv
|
README.md
CHANGED
|
@@ -1,3 +1,112 @@
|
|
| 1 |
-
|
| 2 |
-
|
| 3 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
# Paper Lists
|
| 2 |
+
|
| 3 |
+
This repository powers [Paper Copilot](https://papercopilot.com), combining data from multiple sources to ensure coherence, consistency, and comprehensiveness.
|
| 4 |
+
|
| 5 |
+
Typically, records from OpenReview, official conference sources, or open access sites are scattered, leading to fragmented information and extra effort to navigate between them. The aim of this repository is to serve as a comprehensive link collection for major conferences, enabling easier access to relevant information, and statistical analysis will be based on these records.
|
| 6 |
+
|
| 7 |
+
## Local Search Tool
|
| 8 |
+
We further provide a streamlit-based tool for efficiently searching and analyzing conference papers locally. Thanks to @hhh2210's contribution.
|
| 9 |
+
|
| 10 |
+
### Setup
|
| 11 |
+
```bash
|
| 12 |
+
# Clone the repo and install dependencies
|
| 13 |
+
git clone https://github.com/papercopilot/paperlists.git
|
| 14 |
+
# use conda if needed: conda create -n papercopilot python=3.10
|
| 15 |
+
pip install -r requirements.txt
|
| 16 |
+
```
|
| 17 |
+
|
| 18 |
+
### Usage
|
| 19 |
+
#### 1. Web Interface
|
| 20 |
+
```bash
|
| 21 |
+
cd paperlists/tools
|
| 22 |
+
streamlit run app.py
|
| 23 |
+
# a corresponding local url will popsup, e.g. `Local URL: http://localhost:8501`
|
| 24 |
+
```
|
| 25 |
+

|
| 26 |
+
|
| 27 |
+
#### 2. Command Line Usage
|
| 28 |
+
```bash
|
| 29 |
+
cd paperlists/tools
|
| 30 |
+
python extract.py [keyword] [-i INPUT_PATH] [-o OUTPUT_FILE] [-f FIELDS...]
|
| 31 |
+
```
|
| 32 |
+
|
| 33 |
+
- `keyword`: Search keyword (required)
|
| 34 |
+
- `-i, --input_path`: Input JSON file or directory (default: iclr2025.json)
|
| 35 |
+
- `-o, --output_file`: Output JSON file (optional)
|
| 36 |
+
- `-f, --fields`: Fields to search (default: keywords title primary_area topic)
|
| 37 |
+
|
| 38 |
+
Example:
|
| 39 |
+
```bash
|
| 40 |
+
cd paperlists/tools
|
| 41 |
+
python extract.py retrieval -i iclr/iclr2025.json -o results.json -f title keywords
|
| 42 |
+
```
|
| 43 |
+
|
| 44 |
+
## Overview
|
| 45 |
+
### [ICLR](https://papercopilot.com/statistics/iclr-statistics/)
|
| 46 |
+
| Year | 2025 | 2024 | 2023 | 2022 | 2021 | 2020 |
|
| 47 |
+
|:-:|:-:|:-:|:-:|:-:|:-:|:-:|
|
| 48 |
+
| json | [2025](https://raw.githubusercontent.com/Papercopilot/paperlists/main/iclr/iclr2025.json) | [2024](https://raw.githubusercontent.com/Papercopilot/paperlists/main/iclr/iclr2024.json) | [2023](https://raw.githubusercontent.com/Papercopilot/paperlists/main/iclr/iclr2023.json) | [2022](https://raw.githubusercontent.com/Papercopilot/paperlists/main/iclr/iclr2022.json) | [2021](https://raw.githubusercontent.com/Papercopilot/paperlists/main/iclr/iclr2021.json) | [2020](https://raw.githubusercontent.com/Papercopilot/paperlists/main/iclr/iclr2020.json) |
|
| 49 |
+
| Statistics (Main) | [2025](https://papercopilot.com/statistics/iclr-statistics/iclr-2025-statistics/) | [2024](https://papercopilot.com/statistics/iclr-statistics/iclr-2024-statistics/) | [2023](https://papercopilot.com/statistics/iclr-statistics/iclr-2023-statistics/) | [2022](https://papercopilot.com/statistics/iclr-statistics/iclr-2022-statistics/) | [2021](https://papercopilot.com/statistics/iclr-statistics/iclr-2021-statistics/) | [2020](https://papercopilot.com/statistics/iclr-statistics/iclr-2020-statistics/) |
|
| 50 |
+
|
| 51 |
+
| Year | 2019 | 2018 | 2017 | 2016 | 2015 | 2014 | 2013 |
|
| 52 |
+
|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|
|
| 53 |
+
| json | [2019](https://raw.githubusercontent.com/Papercopilot/paperlists/main/iclr/iclr2019.json) | [2018](https://raw.githubusercontent.com/Papercopilot/paperlists/main/iclr/iclr2018.json) | [2017](https://raw.githubusercontent.com/Papercopilot/paperlists/main/iclr/iclr2017.json) | | | [2014](https://raw.githubusercontent.com/Papercopilot/paperlists/main/iclr/iclr2014.json) | [2013](https://raw.githubusercontent.com/Papercopilot/paperlists/main/iclr/iclr2013.json) |
|
| 54 |
+
| Statistics (Main) | [2019](https://papercopilot.com/statistics/iclr-statistics/iclr-2019-statistics/) | [2018](https://papercopilot.com/statistics/iclr-statistics/iclr-2018-statistics/) | [2017](https://papercopilot.com/statistics/iclr-statistics/iclr-2017-statistics/) | | | [2014](https://papercopilot.com/statistics/iclr-statistics/iclr-2014-statistics/) | [2013](https://papercopilot.com/statistics/iclr-statistics/iclr-2013-statistics/) |
|
| 55 |
+
|
| 56 |
+
### [NeurIPS(NIPS)](https://papercopilot.com/statistics/neurips-statistics/)
|
| 57 |
+
| Year | 2024 | 2023 | 2022 | 2021 | 2020 |
|
| 58 |
+
|:-:|:-:|:-:|:-:|:-:|:-:|
|
| 59 |
+
| json | [2024](https://raw.githubusercontent.com/Papercopilot/paperlists/main/nips/nips2024.json) | [2023](https://raw.githubusercontent.com/Papercopilot/paperlists/main/nips/nips2023.json) | [2022](https://raw.githubusercontent.com/Papercopilot/paperlists/main/nips/nips2022.json) | [2021](https://raw.githubusercontent.com/Papercopilot/paperlists/main/nips/nips2021.json) | [2020](https://raw.githubusercontent.com/Papercopilot/paperlists/main/nips/nips2020.json) |
|
| 60 |
+
| Statistics (Main) | [2024](https://papercopilot.com/statistics/neurips-statistics/neurips-2024-statistics/) | [2023](https://papercopilot.com/statistics/neurips-statistics/neurips-2023-statistics/) | [2022](https://papercopilot.com/statistics/neurips-statistics/neurips-2022-statistics/) | [2021](https://papercopilot.com/statistics/neurips-statistics/neurips-2021-statistics/) | |
|
| 61 |
+
| Statistics (Datasets & Benchmarks) | [2024](https://papercopilot.com/statistics/neurips-statistics/neurips-2024-statistics-datasets-benchmarks/) |[2023](https://papercopilot.com/statistics/neurips-statistics/neurips-2023-statistics-datasets-benchmarks/) | [2022](https://papercopilot.com/statistics/neurips-statistics/neurips-2022-statistics-datasets-benchmarks/) | | |
|
| 62 |
+
|
| 63 |
+
| Year | 2019 | 2018 | 2017 | 2016 | 2015 | 2014 | 2013 | 2012 | 2011 | 2010 |
|
| 64 |
+
|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|
|
| 65 |
+
| json | [2019](https://raw.githubusercontent.com/Papercopilot/paperlists/main/nips/nips2019.json) | [2018](https://raw.githubusercontent.com/Papercopilot/paperlists/main/nips/nips2018.json) | [2017](https://raw.githubusercontent.com/Papercopilot/paperlists/main/nips/nips2017.json) | [2016](https://raw.githubusercontent.com/Papercopilot/paperlists/main/nips/nips2016.json) | [2015](https://raw.githubusercontent.com/Papercopilot/paperlists/main/nips/nips2015.json) | [2014](https://raw.githubusercontent.com/Papercopilot/paperlists/main/nips/nips2014.json) | [2013](https://raw.githubusercontent.com/Papercopilot/paperlists/main/nips/nips2013.json) | [2012](https://raw.githubusercontent.com/Papercopilot/paperlists/main/nips/nips2012.json) | [2011](https://raw.githubusercontent.com/Papercopilot/paperlists/main/nips/nips2011.json) | [2010](https://raw.githubusercontent.com/Papercopilot/paperlists/main/nips/nips2010.json) |
|
| 66 |
+
|
| 67 |
+
| Year | 2009 | 2008 | 2007 | 2006 | 2005 | 2004 | 2003 | 2002 | 2001 | 2000 |
|
| 68 |
+
|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|
|
| 69 |
+
| json | [2009](https://raw.githubusercontent.com/Papercopilot/paperlists/main/nips/nips2009.json) | [2008](https://raw.githubusercontent.com/Papercopilot/paperlists/main/nips/nips2008.json) | [2007](https://raw.githubusercontent.com/Papercopilot/paperlists/main/nips/nips2007.json) | [2006](https://raw.githubusercontent.com/Papercopilot/paperlists/main/nips/nips2006.json) | [2005](https://raw.githubusercontent.com/Papercopilot/paperlists/main/nips/nips2005.json) | [2004](https://raw.githubusercontent.com/Papercopilot/paperlists/main/nips/nips2004.json) | [2003](https://raw.githubusercontent.com/Papercopilot/paperlists/main/nips/nips2003.json) | [2002](https://raw.githubusercontent.com/Papercopilot/paperlists/main/nips/nips2002.json) | [2001](https://raw.githubusercontent.com/Papercopilot/paperlists/main/nips/nips2001.json) | [2000](https://raw.githubusercontent.com/Papercopilot/paperlists/main/nips/nips2000.json) |
|
| 70 |
+
|
| 71 |
+
### [ICML](https://papercopilot.com/statistics/icml-statistics/)
|
| 72 |
+
| Year | 2024 | 2023 | 2022 | 2021 | 2020 | 2019 | 2018 | 2017 |
|
| 73 |
+
|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|
|
| 74 |
+
| json | [2024](https://raw.githubusercontent.com/Papercopilot/paperlists/main/icml/icml2024.json) | [2023](https://raw.githubusercontent.com/Papercopilot/paperlists/main/icml/icml2023.json) | [2022](https://raw.githubusercontent.com/Papercopilot/paperlists/main/icml/icml2022.json) | [2021](https://raw.githubusercontent.com/Papercopilot/paperlists/main/icml/icml2021.json) | [2020](https://raw.githubusercontent.com/Papercopilot/paperlists/main/icml/icml2020.json) | [2019](https://raw.githubusercontent.com/Papercopilot/paperlists/main/icml/icml2019.json) | [2018](https://raw.githubusercontent.com/Papercopilot/paperlists/main/icml/icml2018.json) | [2017](https://raw.githubusercontent.com/Papercopilot/paperlists/main/icml/icml2017.json) |
|
| 75 |
+
|
| 76 |
+
### [SIGGRAPH](https://papercopilot.com/statistics/siggraph-statistics/)
|
| 77 |
+
| Year | 2024 | 2023 | 2022 | 2021 | 2020 |
|
| 78 |
+
|:-:|:-:|:-:|:-:|:-:|:-:|
|
| 79 |
+
| json | [2024](https://raw.githubusercontent.com/Papercopilot/paperlists/main/siggraph/siggraph2024.json) |[2023](https://raw.githubusercontent.com/Papercopilot/paperlists/main/siggraph/siggraph2023.json) | [2022](https://raw.githubusercontent.com/Papercopilot/paperlists/main/siggraph/siggraph2022.json) | [2021](https://raw.githubusercontent.com/Papercopilot/paperlists/main/siggraph/siggraph2021.json) | [2020](https://raw.githubusercontent.com/Papercopilot/paperlists/main/siggraph/siggraph2020.json) |
|
| 80 |
+
| Paperlist | [2024](https://papercopilot.com/paper-list/siggraph-paper-list/siggraph-2024-paper-list/) | [2023](https://papercopilot.com/paper-list/siggraph-paper-list/siggraph-2023-paper-list/) | [2022](https://papercopilot.com/paper-list/siggraph-paper-list/siggraph-2022-paper-list/) | [2021](https://papercopilot.com/paper-list/siggraph-paper-list/siggraph-2021-paper-list/) | [2020](https://papercopilot.com/paper-list/siggraph-paper-list/siggraph-2020-paper-list/) |
|
| 81 |
+
|
| 82 |
+
| Year | 2019 | 2018 | 2017 | 2016 | 2015 | 2014 | 2013 | 2012 | 2011 | 2010 |
|
| 83 |
+
|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|
|
| 84 |
+
| json | [2019](https://raw.githubusercontent.com/Papercopilot/paperlists/main/siggraph/siggraph2019.json) | [2018](https://raw.githubusercontent.com/Papercopilot/paperlists/main/siggraph/siggraph2018.json) | [2017](https://raw.githubusercontent.com/Papercopilot/paperlists/main/siggraph/siggraph2017.json) | [2016](https://raw.githubusercontent.com/Papercopilot/paperlists/main/siggraph/siggraph2016.json) | [2015](https://raw.githubusercontent.com/Papercopilot/paperlists/main/siggraph/siggraph2015.json) | [2014](https://raw.githubusercontent.com/Papercopilot/paperlists/main/siggraph/siggraph2014.json) | [2013](https://raw.githubusercontent.com/Papercopilot/paperlists/main/siggraph/siggraph2013.json) | [2012](https://raw.githubusercontent.com/Papercopilot/paperlists/main/siggraph/siggraph2012.json) | [2011](https://raw.githubusercontent.com/Papercopilot/paperlists/main/siggraph/siggraph2011.json) | [2010](https://raw.githubusercontent.com/Papercopilot/paperlists/main/siggraph/siggraph2010.json) |
|
| 85 |
+
| Paperlist | [2019](https://papercopilot.com/paper-list/siggraph-paper-list/siggraph-2019-paper-list/) | [2018](https://papercopilot.com/paper-list/siggraph-paper-list/siggraph-2018-paper-list/) | [2017](https://papercopilot.com/paper-list/siggraph-paper-list/siggraph-2017-paper-list/) | [2016](https://papercopilot.com/paper-list/siggraph-paper-list/siggraph-2016-paper-list/) | [2015](https://papercopilot.com/paper-list/siggraph-paper-list/siggraph-2015-paper-list/) | [2014](https://papercopilot.com/paper-list/siggraph-paper-list/siggraph-2014-paper-list/) |[2013](https://papercopilot.com/paper-list/siggraph-paper-list/siggraph-2013-paper-list/) |[2012](https://papercopilot.com/paper-list/siggraph-paper-list/siggraph-2012-paper-list/) |[2011](https://papercopilot.com/paper-list/siggraph-paper-list/siggraph-2011-paper-list/) |[2010](https://papercopilot.com/paper-list/siggraph-paper-list/siggraph-2010-paper-list/) |
|
| 86 |
+
|
| 87 |
+
### [SIGGRAPH Asia](https://papercopilot.com/statistics/siggraph-asia-statistics/)
|
| 88 |
+
| Year | 2024 | 2023 | 2022 | 2021 | 2020 | 2019 | 2018 |
|
| 89 |
+
|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|
|
| 90 |
+
| json | [2024](https://raw.githubusercontent.com/Papercopilot/paperlists/main/siggraphasia/siggraphasia2024.json) | [2023](https://raw.githubusercontent.com/Papercopilot/paperlists/main/siggraphasia/siggraphasia2023.json) | [2022](https://raw.githubusercontent.com/Papercopilot/paperlists/main/siggraphasia/siggraphasia2022.json) | [2021](https://raw.githubusercontent.com/Papercopilot/paperlists/main/siggraphasia/siggraphasia2021.json) | [2020](https://raw.githubusercontent.com/Papercopilot/paperlists/main/siggraphasia/siggraphasia2020.json) | [2019](https://raw.githubusercontent.com/Papercopilot/paperlists/main/siggraphasia/siggraphasia2019.json) | [2018](https://raw.githubusercontent.com/Papercopilot/paperlists/main/siggraphasia/siggraphasia2018.json) |
|
| 91 |
+
| Paperlist | [2024](https://papercopilot.com/paper-list/siggraph-asia-paper-list/siggraph-asia-2024-paper-list/) | [2023](https://papercopilot.com/paper-list/siggraph-asia-paper-list/siggraph-asia-2023-paper-list/) | [2022](https://papercopilot.com/paper-list/siggraph-asia-paper-list/siggraph-asia-2022-paper-list/) | [2021](https://papercopilot.com/paper-list/siggraph-asia-paper-list/siggraph-asia-2021-paper-list/) | [2020](https://papercopilot.com/paper-list/siggraph-asia-paper-list/siggraph-asia-2020-paper-list/) | [2019](https://papercopilot.com/paper-list/siggraph-asia-paper-list/siggraph-asia-2019-paper-list/) | [2018](https://papercopilot.com/paper-list/siggraph-asia-paper-list/siggraph-asia-2018-paper-list/) |
|
| 92 |
+
|
| 93 |
+
### CVPR
|
| 94 |
+
| Year | 2024 | 2023 | 2022 | 2021 | 2020 | 2019 | 2018 | 2017 |
|
| 95 |
+
|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|:-:|
|
| 96 |
+
| json | [2024](https://raw.githubusercontent.com/Papercopilot/paperlists/main/cvpr/cvpr2024.json) | [2023](https://raw.githubusercontent.com/Papercopilot/paperlists/main/cvpr/cvpr2023.json) | [2022](https://raw.githubusercontent.com/Papercopilot/paperlists/main/cvpr/cvpr2022.json) | [2021](https://raw.githubusercontent.com/Papercopilot/paperlists/main/cvpr/cvpr2021.json) | [2020](https://raw.githubusercontent.com/Papercopilot/paperlists/main/cvpr/cvpr2020.json) | [2019](https://raw.githubusercontent.com/Papercopilot/paperlists/main/cvpr/cvpr2019.json) | [2018](https://raw.githubusercontent.com/Papercopilot/paperlists/main/cvpr/cvpr2018.json) | [2017](https://raw.githubusercontent.com/Papercopilot/paperlists/main/cvpr/cvpr2017.json) |
|
| 97 |
+
|
| 98 |
+
### ICCV [Coming Soon]
|
| 99 |
+
### ECCV [Coming Soon]
|
| 100 |
+
|
| 101 |
+
### [EMNLP](https://papercopilot.com/statistics/emnlp-statistics/)
|
| 102 |
+
| Year | 2024 |2023 |
|
| 103 |
+
|:-:|:-:|:-:|
|
| 104 |
+
| json | [2024](https://raw.githubusercontent.com/Papercopilot/paperlists/main/emnlp/emnlp2024.json)| [2023](https://raw.githubusercontent.com/Papercopilot/paperlists/main/emnlp/emnlp2023.json) |
|
| 105 |
+
| Statistics | [2024](https://papercopilot.com/statistics/emnlp-statistics/emnlp-2024-statistics/) |[2023](https://papercopilot.com/statistics/emnlp-statistics/emnlp-2023-statistics/) |
|
| 106 |
+
|
| 107 |
+
### [CoRL](https://papercopilot.com/statistics/corl-statistics/)
|
| 108 |
+
| Year | 2024 | 2023 | 2022 | 2021 |
|
| 109 |
+
|:-:|:-:|:-:|:-:|:-:|
|
| 110 |
+
| json | [2024](https://raw.githubusercontent.com/Papercopilot/paperlists/main/corl/corl2024.json) | [2023](https://raw.githubusercontent.com/Papercopilot/paperlists/main/corl/corl2023.json) | [2022](https://raw.githubusercontent.com/Papercopilot/paperlists/main/corl/corl2022.json) | [2021](https://raw.githubusercontent.com/Papercopilot/paperlists/main/corl/corl2021.json) |
|
| 111 |
+
| Statistics | [2024](https://papercopilot.com/statistics/corl-statistics/corl-2024-statistics/) | [2023](https://papercopilot.com/statistics/corl-statistics/corl-2023-statistics/) | [2022](https://papercopilot.com/statistics/corl-statistics/corl-2022-statistics/) | [2021](https://papercopilot.com/statistics/corl-statistics/corl-2021-statistics/) |
|
| 112 |
+
|
aaai/aaai2021.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
aaai/aaai2022.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
aaai/aaai2023.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
aaai/aaai2024.json
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:098627881a4dabfce373d18361f371c37f803309431062f2d0aff6497200f3cd
|
| 3 |
+
size 14216755
|
aaai/aaai2025.json
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:e86d34dedaaa2a6c6fb15983c40851f544efe186ce7b3439f9a7cd617be8e365
|
| 3 |
+
size 17834388
|
acl/acl2021.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
acl/acl2022.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
acl/acl2023.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
acl/acl2024.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
acmmm/acmmm2024.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
aistats/aistats2025.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
colm/colm2024.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
corl/corl2021.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
corl/corl2022.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
corl/corl2023.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
corl/corl2024.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
cvpr/cvpr2013.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
cvpr/cvpr2014.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
cvpr/cvpr2015.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
cvpr/cvpr2016.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
cvpr/cvpr2017.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
cvpr/cvpr2018.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
cvpr/cvpr2019.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
cvpr/cvpr2020.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
cvpr/cvpr2021.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
cvpr/cvpr2022.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
cvpr/cvpr2023.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
cvpr/cvpr2024.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
cvpr/cvpr2025.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
eccv/eccv2018.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
eccv/eccv2020.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
eccv/eccv2022.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
eccv/eccv2024.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
emnlp/emnlp2021.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
emnlp/emnlp2022.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
emnlp/emnlp2023.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
emnlp/emnlp2024.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
iccv/iccv2013.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
iccv/iccv2015.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
iccv/iccv2017.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
iccv/iccv2019.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
iccv/iccv2021.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
iccv/iccv2023.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
iclr/iclr2013.json
ADDED
|
@@ -0,0 +1,1141 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
[
|
| 2 |
+
{
|
| 3 |
+
"id": "-4IA4WgNAy4Wx",
|
| 4 |
+
"title": "What Regularized Auto-Encoders Learn from the Data Generating Distribution",
|
| 5 |
+
"track": "main",
|
| 6 |
+
"status": "Oral",
|
| 7 |
+
"keywords": "",
|
| 8 |
+
"primary_area": "",
|
| 9 |
+
"author": "Guillaume Alain;Yoshua Bengio",
|
| 10 |
+
"authorids": "[email protected];[email protected]",
|
| 11 |
+
"aff": "",
|
| 12 |
+
"aff_domain": "",
|
| 13 |
+
"position": "",
|
| 14 |
+
"rating": "",
|
| 15 |
+
"rating_avg": 0,
|
| 16 |
+
"project": "",
|
| 17 |
+
"github": ""
|
| 18 |
+
},
|
| 19 |
+
{
|
| 20 |
+
"id": "-AIqBI4_qZAQ1",
|
| 21 |
+
"title": "Information Theoretic Learning with Infinitely Divisible Kernels",
|
| 22 |
+
"track": "main",
|
| 23 |
+
"status": "Oral",
|
| 24 |
+
"keywords": "",
|
| 25 |
+
"primary_area": "",
|
| 26 |
+
"author": "Luis Gonzalo S\u00e1nchez;Jose C. Principe",
|
| 27 |
+
"authorids": "[email protected];[email protected]",
|
| 28 |
+
"aff": "",
|
| 29 |
+
"aff_domain": "",
|
| 30 |
+
"position": "",
|
| 31 |
+
"rating": "",
|
| 32 |
+
"rating_avg": 0,
|
| 33 |
+
"project": "",
|
| 34 |
+
"github": ""
|
| 35 |
+
},
|
| 36 |
+
{
|
| 37 |
+
"id": "0OR_OycNMzOF9",
|
| 38 |
+
"title": "Auto-pooling: Learning to Improve Invariance of Image Features from Image Sequences",
|
| 39 |
+
"track": "main",
|
| 40 |
+
"status": "Poster Workshop",
|
| 41 |
+
"keywords": "",
|
| 42 |
+
"primary_area": "",
|
| 43 |
+
"author": "Sainbayar Sukhbaatar;Takaki Makino;Kazuyuki Aihara",
|
| 44 |
+
"authorids": "[email protected];[email protected];[email protected]",
|
| 45 |
+
"aff": "",
|
| 46 |
+
"aff_domain": "",
|
| 47 |
+
"position": "",
|
| 48 |
+
"rating": "",
|
| 49 |
+
"rating_avg": 0,
|
| 50 |
+
"project": "",
|
| 51 |
+
"github": ""
|
| 52 |
+
},
|
| 53 |
+
{
|
| 54 |
+
"id": "0W7-W0EaA4Wak",
|
| 55 |
+
"title": "Joint Training Deep Boltzmann Machines for Classification",
|
| 56 |
+
"track": "main",
|
| 57 |
+
"status": "Oral Workshop",
|
| 58 |
+
"keywords": "",
|
| 59 |
+
"primary_area": "",
|
| 60 |
+
"author": "Ian Goodfellow;Aaron Courville;Yoshua Bengio",
|
| 61 |
+
"authorids": "[email protected];[email protected];[email protected]",
|
| 62 |
+
"aff": "",
|
| 63 |
+
"aff_domain": "",
|
| 64 |
+
"position": "",
|
| 65 |
+
"rating": "",
|
| 66 |
+
"rating_avg": 0,
|
| 67 |
+
"project": "",
|
| 68 |
+
"github": ""
|
| 69 |
+
},
|
| 70 |
+
{
|
| 71 |
+
"id": "11y_SldoumvZl",
|
| 72 |
+
"title": "Factorized Topic Models",
|
| 73 |
+
"track": "main",
|
| 74 |
+
"status": "Poster Workshop",
|
| 75 |
+
"keywords": "",
|
| 76 |
+
"primary_area": "",
|
| 77 |
+
"author": "Cheng Zhang;Carl Henrik Ek;Hedvig Kjellstrom",
|
| 78 |
+
"authorids": "[email protected];[email protected];[email protected]",
|
| 79 |
+
"aff": "",
|
| 80 |
+
"aff_domain": "",
|
| 81 |
+
"position": "",
|
| 82 |
+
"rating": "",
|
| 83 |
+
"rating_avg": 0,
|
| 84 |
+
"project": "",
|
| 85 |
+
"github": ""
|
| 86 |
+
},
|
| 87 |
+
{
|
| 88 |
+
"id": "2LzIDWSabfLe9",
|
| 89 |
+
"title": "Herded Gibbs Sampling",
|
| 90 |
+
"track": "main",
|
| 91 |
+
"status": "Oral",
|
| 92 |
+
"keywords": "",
|
| 93 |
+
"primary_area": "",
|
| 94 |
+
"author": "Luke Bornn;Yutian Chen;Nando de Freitas;Maya Baya;Jing Fang;Max Welling",
|
| 95 | |
| 96 |
+
"aff": "",
|
| 97 |
+
"aff_domain": "",
|
| 98 |
+
"position": "",
|
| 99 |
+
"rating": "",
|
| 100 |
+
"rating_avg": 0,
|
| 101 |
+
"project": "",
|
| 102 |
+
"github": ""
|
| 103 |
+
},
|
| 104 |
+
{
|
| 105 |
+
"id": "2rHk2kZ5knTJ6",
|
| 106 |
+
"title": "A Geometric Descriptor for Cell-Division Detection",
|
| 107 |
+
"track": "main",
|
| 108 |
+
"status": "Reject",
|
| 109 |
+
"keywords": "",
|
| 110 |
+
"primary_area": "",
|
| 111 |
+
"author": "Marcelo Cicconet;Italo Lima;Davi Geiger;Kris Gunsalus",
|
| 112 |
+
"authorids": "[email protected];[email protected];[email protected];[email protected]",
|
| 113 |
+
"aff": "",
|
| 114 |
+
"aff_domain": "",
|
| 115 |
+
"position": "",
|
| 116 |
+
"rating": "",
|
| 117 |
+
"rating_avg": 0,
|
| 118 |
+
"project": "",
|
| 119 |
+
"github": ""
|
| 120 |
+
},
|
| 121 |
+
{
|
| 122 |
+
"id": "3JiGJa1ZBn9W0",
|
| 123 |
+
"title": "The Expressive Power of Word Embeddings",
|
| 124 |
+
"track": "main",
|
| 125 |
+
"status": "Reject",
|
| 126 |
+
"keywords": "",
|
| 127 |
+
"primary_area": "",
|
| 128 |
+
"author": "Yanqing Chen;Bryan P;Rami Al-Rfou;Steven Skiena",
|
| 129 |
+
"authorids": "[email protected];[email protected];[email protected];[email protected]",
|
| 130 |
+
"aff": "",
|
| 131 |
+
"aff_domain": "",
|
| 132 |
+
"position": "",
|
| 133 |
+
"rating": "",
|
| 134 |
+
"rating_avg": 0,
|
| 135 |
+
"project": "",
|
| 136 |
+
"github": ""
|
| 137 |
+
},
|
| 138 |
+
{
|
| 139 |
+
"id": "4UGuUZWZmi4Ze",
|
| 140 |
+
"title": "Feature grouping from spatially constrained multiplicative interaction",
|
| 141 |
+
"track": "main",
|
| 142 |
+
"status": "Oral",
|
| 143 |
+
"keywords": "",
|
| 144 |
+
"primary_area": "",
|
| 145 |
+
"author": "Felix Bauer;Roland Memisevic",
|
| 146 |
+
"authorids": "[email protected];[email protected]",
|
| 147 |
+
"aff": "",
|
| 148 |
+
"aff_domain": "",
|
| 149 |
+
"position": "",
|
| 150 |
+
"rating": "",
|
| 151 |
+
"rating_avg": 0,
|
| 152 |
+
"project": "",
|
| 153 |
+
"github": ""
|
| 154 |
+
},
|
| 155 |
+
{
|
| 156 |
+
"id": "4eEO5rd6xSevQ",
|
| 157 |
+
"title": "Jitter-Adaptive Dictionary Learning - Application to Multi-Trial Neuroelectric Signals",
|
| 158 |
+
"track": "main",
|
| 159 |
+
"status": "Poster",
|
| 160 |
+
"keywords": "",
|
| 161 |
+
"primary_area": "",
|
| 162 |
+
"author": "Sebastian Hitziger;Maureen Clerc;Alexandre Gramfort;Sandrine Saillet;Christian B\u00e9nar;Th\u00e9odore Papadopoulo",
|
| 163 | |
| 164 |
+
"aff": "",
|
| 165 |
+
"aff_domain": "",
|
| 166 |
+
"position": "",
|
| 167 |
+
"rating": "",
|
| 168 |
+
"rating_avg": 0,
|
| 169 |
+
"project": "",
|
| 170 |
+
"github": ""
|
| 171 |
+
},
|
| 172 |
+
{
|
| 173 |
+
"id": "5Qbn4E0Njz4Si",
|
| 174 |
+
"title": "Hierarchical Data Representation Model - Multi-layer NMF",
|
| 175 |
+
"track": "main",
|
| 176 |
+
"status": "Poster Workshop",
|
| 177 |
+
"keywords": "",
|
| 178 |
+
"primary_area": "",
|
| 179 |
+
"author": "Hyun-Ah Song;Soo-Young Lee",
|
| 180 |
+
"authorids": "[email protected];[email protected]",
|
| 181 |
+
"aff": "",
|
| 182 |
+
"aff_domain": "",
|
| 183 |
+
"position": "",
|
| 184 |
+
"rating": "",
|
| 185 |
+
"rating_avg": 0,
|
| 186 |
+
"project": "",
|
| 187 |
+
"github": ""
|
| 188 |
+
},
|
| 189 |
+
{
|
| 190 |
+
"id": "6ZY7ZnIK7kZKy",
|
| 191 |
+
"title": "An Efficient Sufficient Dimension Reduction Method for Identifying Genetic Variants of Clinical Significance",
|
| 192 |
+
"track": "main",
|
| 193 |
+
"status": "Reject",
|
| 194 |
+
"keywords": "",
|
| 195 |
+
"primary_area": "",
|
| 196 |
+
"author": "Momiao Xiong;Long Ma",
|
| 197 |
+
"authorids": "[email protected];Long Ma",
|
| 198 |
+
"aff": "",
|
| 199 |
+
"aff_domain": "",
|
| 200 |
+
"position": "",
|
| 201 |
+
"rating": "",
|
| 202 |
+
"rating_avg": 0,
|
| 203 |
+
"project": "",
|
| 204 |
+
"github": ""
|
| 205 |
+
},
|
| 206 |
+
{
|
| 207 |
+
"id": "6elK6-b28q62g",
|
| 208 |
+
"title": "Behavior Pattern Recognition using A New Representation Model",
|
| 209 |
+
"track": "main",
|
| 210 |
+
"status": "Reject",
|
| 211 |
+
"keywords": "",
|
| 212 |
+
"primary_area": "",
|
| 213 |
+
"author": "Eric qiao;Peter A. Beling",
|
| 214 |
+
"authorids": "[email protected];[email protected]",
|
| 215 |
+
"aff": "",
|
| 216 |
+
"aff_domain": "",
|
| 217 |
+
"position": "",
|
| 218 |
+
"rating": "",
|
| 219 |
+
"rating_avg": 0,
|
| 220 |
+
"project": "",
|
| 221 |
+
"github": ""
|
| 222 |
+
},
|
| 223 |
+
{
|
| 224 |
+
"id": "6s2YsOZPYcb8N",
|
| 225 |
+
"title": "Cutting Recursive Autoencoder Trees",
|
| 226 |
+
"track": "main",
|
| 227 |
+
"status": "Poster",
|
| 228 |
+
"keywords": "",
|
| 229 |
+
"primary_area": "",
|
| 230 |
+
"author": "Christian Scheible;Hinrich Schuetze",
|
| 231 |
+
"authorids": "[email protected];[email protected]",
|
| 232 |
+
"aff": "",
|
| 233 |
+
"aff_domain": "",
|
| 234 |
+
"position": "",
|
| 235 |
+
"rating": "",
|
| 236 |
+
"rating_avg": 0,
|
| 237 |
+
"project": "",
|
| 238 |
+
"github": ""
|
| 239 |
+
},
|
| 240 |
+
{
|
| 241 |
+
"id": "7IOAIAx1AiEYC",
|
| 242 |
+
"title": "Adaptive learning rates and parallelization for stochastic, sparse, non-smooth gradients",
|
| 243 |
+
"track": "main",
|
| 244 |
+
"status": "Poster",
|
| 245 |
+
"keywords": "",
|
| 246 |
+
"primary_area": "",
|
| 247 |
+
"author": "Tom Schaul;Yann LeCun",
|
| 248 |
+
"authorids": "[email protected];[email protected]",
|
| 249 |
+
"aff": "",
|
| 250 |
+
"aff_domain": "",
|
| 251 |
+
"position": "",
|
| 252 |
+
"rating": "",
|
| 253 |
+
"rating_avg": 0,
|
| 254 |
+
"project": "",
|
| 255 |
+
"github": ""
|
| 256 |
+
},
|
| 257 |
+
{
|
| 258 |
+
"id": "7hPJygSqJehqH",
|
| 259 |
+
"title": "Latent Relation Representations for Universal Schemas",
|
| 260 |
+
"track": "main",
|
| 261 |
+
"status": "Poster Workshop",
|
| 262 |
+
"keywords": "",
|
| 263 |
+
"primary_area": "",
|
| 264 |
+
"author": "Sebastian Riedel;Limin Yao;Andrew McCallum",
|
| 265 |
+
"authorids": "[email protected];[email protected];[email protected]",
|
| 266 |
+
"aff": "",
|
| 267 |
+
"aff_domain": "",
|
| 268 |
+
"position": "",
|
| 269 |
+
"rating": "",
|
| 270 |
+
"rating_avg": 0,
|
| 271 |
+
"project": "",
|
| 272 |
+
"github": ""
|
| 273 |
+
},
|
| 274 |
+
{
|
| 275 |
+
"id": "7hXs7GzQHo-QK",
|
| 276 |
+
"title": "The Neural Representation Benchmark and its Evaluation on Brain and Machine",
|
| 277 |
+
"track": "main",
|
| 278 |
+
"status": "Oral",
|
| 279 |
+
"keywords": "",
|
| 280 |
+
"primary_area": "",
|
| 281 |
+
"author": "Charles Cadieu;Ha Hong;Dan Yamins;Nicolas Pinto;Najib J. Majaj;James J. DiCarlo",
|
| 282 | |
| 283 |
+
"aff": "",
|
| 284 |
+
"aff_domain": "",
|
| 285 |
+
"position": "",
|
| 286 |
+
"rating": "",
|
| 287 |
+
"rating_avg": 0,
|
| 288 |
+
"project": "",
|
| 289 |
+
"github": ""
|
| 290 |
+
},
|
| 291 |
+
{
|
| 292 |
+
"id": "9bFY3t2IJ19AC",
|
| 293 |
+
"title": "Affinity Weighted Embedding",
|
| 294 |
+
"track": "main",
|
| 295 |
+
"status": "Oral Workshop",
|
| 296 |
+
"keywords": "",
|
| 297 |
+
"primary_area": "",
|
| 298 |
+
"author": "Jason Weston;Ron Weiss;Hector Yee",
|
| 299 |
+
"authorids": "[email protected];[email protected];[email protected]",
|
| 300 |
+
"aff": "",
|
| 301 |
+
"aff_domain": "",
|
| 302 |
+
"position": "",
|
| 303 |
+
"rating": "",
|
| 304 |
+
"rating_avg": 0,
|
| 305 |
+
"project": "",
|
| 306 |
+
"github": ""
|
| 307 |
+
},
|
| 308 |
+
{
|
| 309 |
+
"id": "ACBmCbico7jkg",
|
| 310 |
+
"title": "Gradient Driven Learning for Pooling in Visual Pipeline Feature Extraction Models",
|
| 311 |
+
"track": "main",
|
| 312 |
+
"status": "Poster Workshop",
|
| 313 |
+
"keywords": "",
|
| 314 |
+
"primary_area": "",
|
| 315 |
+
"author": "Derek Rose;Itamar Arel",
|
| 316 |
+
"authorids": "[email protected];[email protected]",
|
| 317 |
+
"aff": "",
|
| 318 |
+
"aff_domain": "",
|
| 319 |
+
"position": "",
|
| 320 |
+
"rating": "",
|
| 321 |
+
"rating_avg": 0,
|
| 322 |
+
"project": "",
|
| 323 |
+
"github": ""
|
| 324 |
+
},
|
| 325 |
+
{
|
| 326 |
+
"id": "BBIbj9w8Lvj8F",
|
| 327 |
+
"title": "Efficient Learning of Domain-invariant Image Representations",
|
| 328 |
+
"track": "main",
|
| 329 |
+
"status": "Oral",
|
| 330 |
+
"keywords": "",
|
| 331 |
+
"primary_area": "",
|
| 332 |
+
"author": "Judy Hoffman;Erik Rodner;Jeff Donahue;Kate Saenko;Trevor Darrell",
|
| 333 |
+
"authorids": "[email protected];[email protected];[email protected];[email protected];[email protected]",
|
| 334 |
+
"aff": "",
|
| 335 |
+
"aff_domain": "",
|
| 336 |
+
"position": "",
|
| 337 |
+
"rating": "",
|
| 338 |
+
"rating_avg": 0,
|
| 339 |
+
"project": "",
|
| 340 |
+
"github": ""
|
| 341 |
+
},
|
| 342 |
+
{
|
| 343 |
+
"id": "BmOABAaTQDmt2",
|
| 344 |
+
"title": "A Semantic Matching Energy Function for Learning with Multi-relational Data",
|
| 345 |
+
"track": "main",
|
| 346 |
+
"status": "Poster Workshop",
|
| 347 |
+
"keywords": "",
|
| 348 |
+
"primary_area": "",
|
| 349 |
+
"author": "Xavier Glorot;Antoine Bordes;Jason Weston;Yoshua Bengio",
|
| 350 |
+
"authorids": "[email protected];[email protected];[email protected];[email protected]",
|
| 351 |
+
"aff": "",
|
| 352 |
+
"aff_domain": "",
|
| 353 |
+
"position": "",
|
| 354 |
+
"rating": "",
|
| 355 |
+
"rating_avg": 0,
|
| 356 |
+
"project": "",
|
| 357 |
+
"github": ""
|
| 358 |
+
},
|
| 359 |
+
{
|
| 360 |
+
"id": "DD2gbWiOgJDmY",
|
| 361 |
+
"title": "Why Size Matters: Feature Coding as Nystrom Sampling",
|
| 362 |
+
"track": "main",
|
| 363 |
+
"status": "Oral Workshop",
|
| 364 |
+
"keywords": "",
|
| 365 |
+
"primary_area": "",
|
| 366 |
+
"author": "Oriol Vinyals;Yangqing Jia;Trevor Darrell",
|
| 367 |
+
"authorids": "[email protected];[email protected];[email protected]",
|
| 368 |
+
"aff": "",
|
| 369 |
+
"aff_domain": "",
|
| 370 |
+
"position": "",
|
| 371 |
+
"rating": "",
|
| 372 |
+
"rating_avg": 0,
|
| 373 |
+
"project": "",
|
| 374 |
+
"github": ""
|
| 375 |
+
},
|
| 376 |
+
{
|
| 377 |
+
"id": "G0OapcfeK3g_R",
|
| 378 |
+
"title": "Block Coordinate Descent for Sparse NMF",
|
| 379 |
+
"track": "main",
|
| 380 |
+
"status": "Poster",
|
| 381 |
+
"keywords": "",
|
| 382 |
+
"primary_area": "",
|
| 383 |
+
"author": "Vamsi Potluru;Sergey M. Plis;Jonathan Le Roux;Barak A. Pearlmutter;Vince D. Calhoun;Thomas P. Hayes",
|
| 384 | |
| 385 |
+
"aff": "",
|
| 386 |
+
"aff_domain": "",
|
| 387 |
+
"position": "",
|
| 388 |
+
"rating": "",
|
| 389 |
+
"rating_avg": 0,
|
| 390 |
+
"project": "",
|
| 391 |
+
"github": ""
|
| 392 |
+
},
|
| 393 |
+
{
|
| 394 |
+
"id": "GgtWGz7e5_MeB",
|
| 395 |
+
"title": "Joint Space Neural Probabilistic Language Model for Statistical Machine Translation",
|
| 396 |
+
"track": "main",
|
| 397 |
+
"status": "Reject",
|
| 398 |
+
"keywords": "",
|
| 399 |
+
"primary_area": "",
|
| 400 |
+
"author": "Tsuyoshi Okita",
|
| 401 |
+
"authorids": "[email protected]",
|
| 402 |
+
"aff": "",
|
| 403 |
+
"aff_domain": "",
|
| 404 |
+
"position": "",
|
| 405 |
+
"rating": "",
|
| 406 |
+
"rating_avg": 0,
|
| 407 |
+
"project": "",
|
| 408 |
+
"github": ""
|
| 409 |
+
},
|
| 410 |
+
{
|
| 411 |
+
"id": "IpmfpAGoH2KbX",
|
| 412 |
+
"title": "Deep learning and the renormalization group",
|
| 413 |
+
"track": "main",
|
| 414 |
+
"status": "Reject",
|
| 415 |
+
"keywords": "",
|
| 416 |
+
"primary_area": "",
|
| 417 |
+
"author": "C\u00e9dric B\u00e9ny",
|
| 418 |
+
"authorids": "[email protected]",
|
| 419 |
+
"aff": "",
|
| 420 |
+
"aff_domain": "",
|
| 421 |
+
"position": "",
|
| 422 |
+
"rating": "",
|
| 423 |
+
"rating_avg": 0,
|
| 424 |
+
"project": "",
|
| 425 |
+
"github": ""
|
| 426 |
+
},
|
| 427 |
+
{
|
| 428 |
+
"id": "KHMdKiX2lbguE",
|
| 429 |
+
"title": "Boltzmann Machines and Denoising Autoencoders for Image Denoising",
|
| 430 |
+
"track": "main",
|
| 431 |
+
"status": "Poster Workshop",
|
| 432 |
+
"keywords": "",
|
| 433 |
+
"primary_area": "",
|
| 434 |
+
"author": "KyungHyun Cho",
|
| 435 |
+
"authorids": "[email protected]",
|
| 436 |
+
"aff": "",
|
| 437 |
+
"aff_domain": "",
|
| 438 |
+
"position": "",
|
| 439 |
+
"rating": "",
|
| 440 |
+
"rating_avg": 0,
|
| 441 |
+
"project": "",
|
| 442 |
+
"github": ""
|
| 443 |
+
},
|
| 444 |
+
{
|
| 445 |
+
"id": "KKZ-FeUj-9kjY",
|
| 446 |
+
"title": "Sparse Penalty in Deep Belief Networks: Using the Mixed Norm Constraint",
|
| 447 |
+
"track": "main",
|
| 448 |
+
"status": "Reject",
|
| 449 |
+
"keywords": "",
|
| 450 |
+
"primary_area": "",
|
| 451 |
+
"author": "Xanadu Halkias;S\u00e9bastien PARIS;Herve Glotin",
|
| 452 |
+
"authorids": "[email protected];[email protected];glotin.univ-tln.fr",
|
| 453 |
+
"aff": "",
|
| 454 |
+
"aff_domain": "",
|
| 455 |
+
"position": "",
|
| 456 |
+
"rating": "",
|
| 457 |
+
"rating_avg": 0,
|
| 458 |
+
"project": "",
|
| 459 |
+
"github": ""
|
| 460 |
+
},
|
| 461 |
+
{
|
| 462 |
+
"id": "MQm0HKx20L7iN",
|
| 463 |
+
"title": "Kernelized Locality-Sensitive Hashing for Semi-Supervised Agglomerative Clustering",
|
| 464 |
+
"track": "main",
|
| 465 |
+
"status": "Reject",
|
| 466 |
+
"keywords": "",
|
| 467 |
+
"primary_area": "",
|
| 468 |
+
"author": "Boyi Xie;Shuheng Zheng",
|
| 469 |
+
"authorids": "[email protected];[email protected]",
|
| 470 |
+
"aff": "",
|
| 471 |
+
"aff_domain": "",
|
| 472 |
+
"position": "",
|
| 473 |
+
"rating": "",
|
| 474 |
+
"rating_avg": 0,
|
| 475 |
+
"project": "",
|
| 476 |
+
"github": ""
|
| 477 |
+
},
|
| 478 |
+
{
|
| 479 |
+
"id": "N_c1XDpyus_yP",
|
| 480 |
+
"title": "A Nested HDP for Hierarchical Topic Models",
|
| 481 |
+
"track": "main",
|
| 482 |
+
"status": "Oral Workshop",
|
| 483 |
+
"keywords": "",
|
| 484 |
+
"primary_area": "",
|
| 485 |
+
"author": "John Paisley;Chong Wang;David Blei;Michael I. Jordan",
|
| 486 |
+
"authorids": "[email protected];[email protected];[email protected];[email protected]",
|
| 487 |
+
"aff": "",
|
| 488 |
+
"aff_domain": "",
|
| 489 |
+
"position": "",
|
| 490 |
+
"rating": "",
|
| 491 |
+
"rating_avg": 0,
|
| 492 |
+
"project": "",
|
| 493 |
+
"github": ""
|
| 494 |
+
},
|
| 495 |
+
{
|
| 496 |
+
"id": "OOuGtqpeK-cLI",
|
| 497 |
+
"title": "Pushing Stochastic Gradient towards Second-Order Methods -- Backpropagation Learning with Transformations in Nonlinearities",
|
| 498 |
+
"track": "main",
|
| 499 |
+
"status": "Poster Workshop",
|
| 500 |
+
"keywords": "",
|
| 501 |
+
"primary_area": "",
|
| 502 |
+
"author": "Tommi Vatanen;Tapani Raiko;Harri Valpola;Yann LeCun",
|
| 503 |
+
"authorids": "[email protected];[email protected];[email protected];[email protected]",
|
| 504 |
+
"aff": "",
|
| 505 |
+
"aff_domain": "",
|
| 506 |
+
"position": "",
|
| 507 |
+
"rating": "",
|
| 508 |
+
"rating_avg": 0,
|
| 509 |
+
"project": "",
|
| 510 |
+
"github": ""
|
| 511 |
+
},
|
| 512 |
+
{
|
| 513 |
+
"id": "OVyHViMbHRm8c",
|
| 514 |
+
"title": "Visual Objects Classification with Sliding Spatial Pyramid Matching",
|
| 515 |
+
"track": "main",
|
| 516 |
+
"status": "Poster Workshop",
|
| 517 |
+
"keywords": "",
|
| 518 |
+
"primary_area": "",
|
| 519 |
+
"author": "Hao Wooi Lim;Yong Haur Tay",
|
| 520 |
+
"authorids": "[email protected];[email protected]",
|
| 521 |
+
"aff": "",
|
| 522 |
+
"aff_domain": "",
|
| 523 |
+
"position": "",
|
| 524 |
+
"rating": "",
|
| 525 |
+
"rating_avg": 0,
|
| 526 |
+
"project": "",
|
| 527 |
+
"github": ""
|
| 528 |
+
},
|
| 529 |
+
{
|
| 530 |
+
"id": "OpvgONa-3WODz",
|
| 531 |
+
"title": "Metric-Free Natural Gradient for Joint-Training of Boltzmann Machines",
|
| 532 |
+
"track": "main",
|
| 533 |
+
"status": "Poster",
|
| 534 |
+
"keywords": "",
|
| 535 |
+
"primary_area": "",
|
| 536 |
+
"author": "Guillaume Desjardins;Razvan Pascanu;Aaron Courville;Yoshua Bengio",
|
| 537 |
+
"authorids": "[email protected];[email protected];[email protected];[email protected]",
|
| 538 |
+
"aff": "",
|
| 539 |
+
"aff_domain": "",
|
| 540 |
+
"position": "",
|
| 541 |
+
"rating": "",
|
| 542 |
+
"rating_avg": 0,
|
| 543 |
+
"project": "",
|
| 544 |
+
"github": ""
|
| 545 |
+
},
|
| 546 |
+
{
|
| 547 |
+
"id": "OznsOsb6sDFeV",
|
| 548 |
+
"title": "Unsupervised Feature Learning for low-level Local Image Descriptors",
|
| 549 |
+
"track": "main",
|
| 550 |
+
"status": "Poster Workshop",
|
| 551 |
+
"keywords": "",
|
| 552 |
+
"primary_area": "",
|
| 553 |
+
"author": "Christian Osendorfer;Justin Bayer;Patrick van der Smagt",
|
| 554 |
+
"authorids": "[email protected];[email protected];[email protected]",
|
| 555 |
+
"aff": "",
|
| 556 |
+
"aff_domain": "",
|
| 557 |
+
"position": "",
|
| 558 |
+
"rating": "",
|
| 559 |
+
"rating_avg": 0,
|
| 560 |
+
"project": "",
|
| 561 |
+
"github": ""
|
| 562 |
+
},
|
| 563 |
+
{
|
| 564 |
+
"id": "PRuOK_LY_WPIq",
|
| 565 |
+
"title": "Matrix Approximation under Local Low-Rank Assumption",
|
| 566 |
+
"track": "main",
|
| 567 |
+
"status": "Poster Workshop",
|
| 568 |
+
"keywords": "",
|
| 569 |
+
"primary_area": "",
|
| 570 |
+
"author": "Joonseok Lee;Seungyeon Kim;Guy Lebanon;Yoram Singer",
|
| 571 |
+
"authorids": "[email protected];[email protected];[email protected];[email protected]",
|
| 572 |
+
"aff": "",
|
| 573 |
+
"aff_domain": "",
|
| 574 |
+
"position": "",
|
| 575 |
+
"rating": "",
|
| 576 |
+
"rating_avg": 0,
|
| 577 |
+
"project": "",
|
| 578 |
+
"github": ""
|
| 579 |
+
},
|
| 580 |
+
{
|
| 581 |
+
"id": "SSnY462CYz1Cu",
|
| 582 |
+
"title": "Knowledge Matters: Importance of Prior Information for Optimization",
|
| 583 |
+
"track": "main",
|
| 584 |
+
"status": "Oral",
|
| 585 |
+
"keywords": "",
|
| 586 |
+
"primary_area": "",
|
| 587 |
+
"author": "\u00c7a\u011flar G\u00fcl\u00e7ehre;Yoshua Bengio",
|
| 588 |
+
"authorids": "[email protected];[email protected]",
|
| 589 |
+
"aff": "",
|
| 590 |
+
"aff_domain": "",
|
| 591 |
+
"position": "",
|
| 592 |
+
"rating": "",
|
| 593 |
+
"rating_avg": 0,
|
| 594 |
+
"project": "",
|
| 595 |
+
"github": ""
|
| 596 |
+
},
|
| 597 |
+
{
|
| 598 |
+
"id": "SqNvxV9FQoSk2",
|
| 599 |
+
"title": "Switched linear encoding with rectified linear autoencoders",
|
| 600 |
+
"track": "main",
|
| 601 |
+
"status": "Reject",
|
| 602 |
+
"keywords": "",
|
| 603 |
+
"primary_area": "",
|
| 604 |
+
"author": "Leif Johnson;Craig Corcoran",
|
| 605 |
+
"authorids": "[email protected];[email protected]",
|
| 606 |
+
"aff": "",
|
| 607 |
+
"aff_domain": "",
|
| 608 |
+
"position": "",
|
| 609 |
+
"rating": "",
|
| 610 |
+
"rating_avg": 0,
|
| 611 |
+
"project": "",
|
| 612 |
+
"github": ""
|
| 613 |
+
},
|
| 614 |
+
{
|
| 615 |
+
"id": "TT0bFo9VZpFWg",
|
| 616 |
+
"title": "Big Neural Networks Waste Capacity",
|
| 617 |
+
"track": "main",
|
| 618 |
+
"status": "Oral Workshop",
|
| 619 |
+
"keywords": "",
|
| 620 |
+
"primary_area": "",
|
| 621 |
+
"author": "Yann Dauphin;Yoshua Bengio",
|
| 622 |
+
"authorids": "[email protected];[email protected]",
|
| 623 |
+
"aff": "",
|
| 624 |
+
"aff_domain": "",
|
| 625 |
+
"position": "",
|
| 626 |
+
"rating": "",
|
| 627 |
+
"rating_avg": 0,
|
| 628 |
+
"project": "",
|
| 629 |
+
"github": ""
|
| 630 |
+
},
|
| 631 |
+
{
|
| 632 |
+
"id": "UUwuUaQ5qRyWn",
|
| 633 |
+
"title": "When Does a Mixture of Products Contain a Product of Mixtures?",
|
| 634 |
+
"track": "main",
|
| 635 |
+
"status": "Poster Workshop",
|
| 636 |
+
"keywords": "",
|
| 637 |
+
"primary_area": "",
|
| 638 |
+
"author": "Guido F. Montufar;Jason Morton",
|
| 639 |
+
"authorids": "[email protected];[email protected]",
|
| 640 |
+
"aff": "",
|
| 641 |
+
"aff_domain": "",
|
| 642 |
+
"position": "",
|
| 643 |
+
"rating": "",
|
| 644 |
+
"rating_avg": 0,
|
| 645 |
+
"project": "",
|
| 646 |
+
"github": ""
|
| 647 |
+
},
|
| 648 |
+
{
|
| 649 |
+
"id": "V_-8VUqv8h_H3",
|
| 650 |
+
"title": "The Manifold of Human Emotions",
|
| 651 |
+
"track": "main",
|
| 652 |
+
"status": "Poster Workshop",
|
| 653 |
+
"keywords": "",
|
| 654 |
+
"primary_area": "",
|
| 655 |
+
"author": "Seungyeon Kim;Fuxin Li;Guy Lebanon;Irfan Essa",
|
| 656 |
+
"authorids": "[email protected];[email protected];[email protected];[email protected]",
|
| 657 |
+
"aff": "",
|
| 658 |
+
"aff_domain": "",
|
| 659 |
+
"position": "",
|
| 660 |
+
"rating": "",
|
| 661 |
+
"rating_avg": 0,
|
| 662 |
+
"project": "",
|
| 663 |
+
"github": ""
|
| 664 |
+
},
|
| 665 |
+
{
|
| 666 |
+
"id": "YBi6KFA7PfKo5",
|
| 667 |
+
"title": "Two SVDs produce more focal deep learning representations",
|
| 668 |
+
"track": "main",
|
| 669 |
+
"status": "Poster Workshop",
|
| 670 |
+
"keywords": "",
|
| 671 |
+
"primary_area": "",
|
| 672 |
+
"author": "Hinrich Schuetze;Christian Scheible",
|
| 673 |
+
"authorids": "[email protected];[email protected]",
|
| 674 |
+
"aff": "",
|
| 675 |
+
"aff_domain": "",
|
| 676 |
+
"position": "",
|
| 677 |
+
"rating": "",
|
| 678 |
+
"rating_avg": 0,
|
| 679 |
+
"project": "",
|
| 680 |
+
"github": ""
|
| 681 |
+
},
|
| 682 |
+
{
|
| 683 |
+
"id": "ZhGJ9KQlXi9jk",
|
| 684 |
+
"title": "Complexity of Representation and Inference in Compositional Models with Part Sharing",
|
| 685 |
+
"track": "main",
|
| 686 |
+
"status": "Oral",
|
| 687 |
+
"keywords": "",
|
| 688 |
+
"primary_area": "",
|
| 689 |
+
"author": "Alan Yuille;Roozbeh Mottaghi",
|
| 690 |
+
"authorids": "[email protected];[email protected]",
|
| 691 |
+
"aff": "",
|
| 692 |
+
"aff_domain": "",
|
| 693 |
+
"position": "",
|
| 694 |
+
"rating": "",
|
| 695 |
+
"rating_avg": 0,
|
| 696 |
+
"project": "",
|
| 697 |
+
"github": ""
|
| 698 |
+
},
|
| 699 |
+
{
|
| 700 |
+
"id": "aJh-lFL2dFJ21",
|
| 701 |
+
"title": "Discriminative Recurrent Sparse Auto-Encoders",
|
| 702 |
+
"track": "main",
|
| 703 |
+
"status": "Oral",
|
| 704 |
+
"keywords": "",
|
| 705 |
+
"primary_area": "",
|
| 706 |
+
"author": "Jason Rolfe;Yann LeCun",
|
| 707 |
+
"authorids": "[email protected];[email protected]",
|
| 708 |
+
"aff": "",
|
| 709 |
+
"aff_domain": "",
|
| 710 |
+
"position": "",
|
| 711 |
+
"rating": "",
|
| 712 |
+
"rating_avg": 0,
|
| 713 |
+
"project": "",
|
| 714 |
+
"github": ""
|
| 715 |
+
},
|
| 716 |
+
{
|
| 717 |
+
"id": "aQZtOGDyp-Ozh",
|
| 718 |
+
"title": "Learning Stable Group Invariant Representations with Convolutional Networks",
|
| 719 |
+
"track": "main",
|
| 720 |
+
"status": "Poster Workshop",
|
| 721 |
+
"keywords": "",
|
| 722 |
+
"primary_area": "",
|
| 723 |
+
"author": "Joan Bruna;Arthur Szlam;Yann LeCun",
|
| 724 |
+
"authorids": "[email protected];[email protected];[email protected]",
|
| 725 |
+
"aff": "",
|
| 726 |
+
"aff_domain": "",
|
| 727 |
+
"position": "",
|
| 728 |
+
"rating": "",
|
| 729 |
+
"rating_avg": 0,
|
| 730 |
+
"project": "",
|
| 731 |
+
"github": ""
|
| 732 |
+
},
|
| 733 |
+
{
|
| 734 |
+
"id": "bI58OFtQlLOQ7",
|
| 735 |
+
"title": "Deep Learning for Detecting Robotic Grasps",
|
| 736 |
+
"track": "main",
|
| 737 |
+
"status": "Oral Workshop",
|
| 738 |
+
"keywords": "",
|
| 739 |
+
"primary_area": "",
|
| 740 |
+
"author": "Ian Lenz;Honglak Lee;Ashutosh Saxena",
|
| 741 |
+
"authorids": "[email protected];[email protected];[email protected]",
|
| 742 |
+
"aff": "",
|
| 743 |
+
"aff_domain": "",
|
| 744 |
+
"position": "",
|
| 745 |
+
"rating": "",
|
| 746 |
+
"rating_avg": 0,
|
| 747 |
+
"project": "",
|
| 748 |
+
"github": ""
|
| 749 |
+
},
|
| 750 |
+
{
|
| 751 |
+
"id": "eQWJec0ursynH",
|
| 752 |
+
"title": "Barnes-Hut-SNE",
|
| 753 |
+
"track": "main",
|
| 754 |
+
"status": "Oral",
|
| 755 |
+
"keywords": "",
|
| 756 |
+
"primary_area": "",
|
| 757 |
+
"author": "Laurens van der Maaten",
|
| 758 |
+
"authorids": "[email protected]",
|
| 759 |
+
"aff": "",
|
| 760 |
+
"aff_domain": "",
|
| 761 |
+
"position": "",
|
| 762 |
+
"rating": "",
|
| 763 |
+
"rating_avg": 0,
|
| 764 |
+
"project": "",
|
| 765 |
+
"github": ""
|
| 766 |
+
},
|
| 767 |
+
{
|
| 768 |
+
"id": "fm5jfAwPbOfP6",
|
| 769 |
+
"title": "Linear-Nonlinear-Poisson Neuron Networks Perform Bayesian Inference On Boltzmann Machines",
|
| 770 |
+
"track": "main",
|
| 771 |
+
"status": "Poster Workshop",
|
| 772 |
+
"keywords": "",
|
| 773 |
+
"primary_area": "",
|
| 774 |
+
"author": "Yuanlong Shao",
|
| 775 |
+
"authorids": "[email protected]",
|
| 776 |
+
"aff": "",
|
| 777 |
+
"aff_domain": "",
|
| 778 |
+
"position": "",
|
| 779 |
+
"rating": "",
|
| 780 |
+
"rating_avg": 0,
|
| 781 |
+
"project": "",
|
| 782 |
+
"github": ""
|
| 783 |
+
},
|
| 784 |
+
{
|
| 785 |
+
"id": "g6Jl6J3aMs6a7",
|
| 786 |
+
"title": "Recurrent Online Clustering as a Spatio-Temporal Feature Extractor in DeSTIN",
|
| 787 |
+
"track": "main",
|
| 788 |
+
"status": "Reject",
|
| 789 |
+
"keywords": "",
|
| 790 |
+
"primary_area": "",
|
| 791 |
+
"author": "Steven R. Young;Itamar Arel",
|
| 792 |
+
"authorids": "[email protected];[email protected]",
|
| 793 |
+
"aff": "",
|
| 794 |
+
"aff_domain": "",
|
| 795 |
+
"position": "",
|
| 796 |
+
"rating": "",
|
| 797 |
+
"rating_avg": 0,
|
| 798 |
+
"project": "",
|
| 799 |
+
"github": ""
|
| 800 |
+
},
|
| 801 |
+
{
|
| 802 |
+
"id": "gGivgRWZsLgY0",
|
| 803 |
+
"title": "Clustering Learning for Robotic Vision",
|
| 804 |
+
"track": "main",
|
| 805 |
+
"status": "Poster Workshop",
|
| 806 |
+
"keywords": "",
|
| 807 |
+
"primary_area": "",
|
| 808 |
+
"author": "Eugenio Culurciello;Jordan Bates;Aysegul Dundar;Jose Carrasco;Clement Farabet",
|
| 809 |
+
"authorids": "[email protected];[email protected];[email protected];[email protected];[email protected]",
|
| 810 |
+
"aff": "",
|
| 811 |
+
"aff_domain": "",
|
| 812 |
+
"position": "",
|
| 813 |
+
"rating": "",
|
| 814 |
+
"rating_avg": 0,
|
| 815 |
+
"project": "",
|
| 816 |
+
"github": ""
|
| 817 |
+
},
|
| 818 |
+
{
|
| 819 |
+
"id": "i87JIQTAnB8AQ",
|
| 820 |
+
"title": "The Diagonalized Newton Algorithm for Nonnegative Matrix Factorization",
|
| 821 |
+
"track": "main",
|
| 822 |
+
"status": "Poster",
|
| 823 |
+
"keywords": "",
|
| 824 |
+
"primary_area": "",
|
| 825 |
+
"author": "Hugo Van hamme",
|
| 826 |
+
"authorids": "[email protected]",
|
| 827 |
+
"aff": "",
|
| 828 |
+
"aff_domain": "",
|
| 829 |
+
"position": "",
|
| 830 |
+
"rating": "",
|
| 831 |
+
"rating_avg": 0,
|
| 832 |
+
"project": "",
|
| 833 |
+
"github": ""
|
| 834 |
+
},
|
| 835 |
+
{
|
| 836 |
+
"id": "iKeAKFLmxoim3",
|
| 837 |
+
"title": "Heteroscedastic Conditional Ordinal Random Fields for Pain Intensity Estimation from Facial Images",
|
| 838 |
+
"track": "main",
|
| 839 |
+
"status": "Reject",
|
| 840 |
+
"keywords": "",
|
| 841 |
+
"primary_area": "",
|
| 842 |
+
"author": "Ognjen Rudovic;Maja Pantic;Vladimir Pavlovic",
|
| 843 |
+
"authorids": "[email protected];[email protected];[email protected]",
|
| 844 |
+
"aff": "",
|
| 845 |
+
"aff_domain": "",
|
| 846 |
+
"position": "",
|
| 847 |
+
"rating": "",
|
| 848 |
+
"rating_avg": 0,
|
| 849 |
+
"project": "",
|
| 850 |
+
"github": ""
|
| 851 |
+
},
|
| 852 |
+
{
|
| 853 |
+
"id": "idpCdOWtqXd60",
|
| 854 |
+
"title": "Efficient Estimation of Word Representations in Vector Space",
|
| 855 |
+
"track": "main",
|
| 856 |
+
"status": "Poster Workshop",
|
| 857 |
+
"keywords": "",
|
| 858 |
+
"primary_area": "",
|
| 859 |
+
"author": "Tomas Mikolov;Kai Chen;Greg Corrado;Jeffrey Dean",
|
| 860 |
+
"authorids": "[email protected];[email protected];[email protected];[email protected]",
|
| 861 |
+
"aff": "",
|
| 862 |
+
"aff_domain": "",
|
| 863 |
+
"position": "",
|
| 864 |
+
"rating": "",
|
| 865 |
+
"rating_avg": 0,
|
| 866 |
+
"project": "",
|
| 867 |
+
"github": ""
|
| 868 |
+
},
|
| 869 |
+
{
|
| 870 |
+
"id": "jbLdjjxPd-b2l",
|
| 871 |
+
"title": "Natural Gradient Revisited",
|
| 872 |
+
"track": "main",
|
| 873 |
+
"status": "Poster Workshop",
|
| 874 |
+
"keywords": "",
|
| 875 |
+
"primary_area": "",
|
| 876 |
+
"author": "Razvan Pascanu;Yoshua Bengio",
|
| 877 |
+
"authorids": "[email protected];[email protected]",
|
| 878 |
+
"aff": "",
|
| 879 |
+
"aff_domain": "",
|
| 880 |
+
"position": "",
|
| 881 |
+
"rating": "",
|
| 882 |
+
"rating_avg": 0,
|
| 883 |
+
"project": "",
|
| 884 |
+
"github": ""
|
| 885 |
+
},
|
| 886 |
+
{
|
| 887 |
+
"id": "kk_XkMO0-dP8W",
|
| 888 |
+
"title": "Feature Learning in Deep Neural Networks - A Study on Speech Recognition Tasks",
|
| 889 |
+
"track": "main",
|
| 890 |
+
"status": "Oral",
|
| 891 |
+
"keywords": "",
|
| 892 |
+
"primary_area": "",
|
| 893 |
+
"author": "Dong Yu;Mike Seltzer;Jinyu Li;Jui-Ting Huang;Frank Seide",
|
| 894 |
+
"authorids": "[email protected];[email protected];[email protected];[email protected];[email protected]",
|
| 895 |
+
"aff": "",
|
| 896 |
+
"aff_domain": "",
|
| 897 |
+
"position": "",
|
| 898 |
+
"rating": "",
|
| 899 |
+
"rating_avg": 0,
|
| 900 |
+
"project": "",
|
| 901 |
+
"github": ""
|
| 902 |
+
},
|
| 903 |
+
{
|
| 904 |
+
"id": "l_PClqDdLb5Bp",
|
| 905 |
+
"title": "Stochastic Pooling for Regularization of Deep Convolutional Neural Networks",
|
| 906 |
+
"track": "main",
|
| 907 |
+
"status": "Oral",
|
| 908 |
+
"keywords": "",
|
| 909 |
+
"primary_area": "",
|
| 910 |
+
"author": "Matthew Zeiler;Rob Fergus",
|
| 911 |
+
"authorids": "[email protected];[email protected]",
|
| 912 |
+
"aff": "",
|
| 913 |
+
"aff_domain": "",
|
| 914 |
+
"position": "",
|
| 915 |
+
"rating": "",
|
| 916 |
+
"rating_avg": 0,
|
| 917 |
+
"project": "",
|
| 918 |
+
"github": ""
|
| 919 |
+
},
|
| 920 |
+
{
|
| 921 |
+
"id": "mLr3In-nbamNu",
|
| 922 |
+
"title": "Local Component Analysis",
|
| 923 |
+
"track": "main",
|
| 924 |
+
"status": "Poster",
|
| 925 |
+
"keywords": "",
|
| 926 |
+
"primary_area": "",
|
| 927 |
+
"author": "Nicolas Le Roux;Francis Bach",
|
| 928 |
+
"authorids": "[email protected];[email protected]",
|
| 929 |
+
"aff": "",
|
| 930 |
+
"aff_domain": "",
|
| 931 |
+
"position": "",
|
| 932 |
+
"rating": "",
|
| 933 |
+
"rating_avg": 0,
|
| 934 |
+
"project": "",
|
| 935 |
+
"github": ""
|
| 936 |
+
},
|
| 937 |
+
{
|
| 938 |
+
"id": "msGKsXQXNiCBk",
|
| 939 |
+
"title": "Learning New Facts From Knowledge Bases With Neural Tensor Networks and Semantic Word Vectors",
|
| 940 |
+
"track": "main",
|
| 941 |
+
"status": "Poster Workshop",
|
| 942 |
+
"keywords": "",
|
| 943 |
+
"primary_area": "",
|
| 944 |
+
"author": "Danqi Chen;Richard Socher;Christopher Manning;Andrew Y. Ng",
|
| 945 |
+
"authorids": "[email protected];[email protected];[email protected];[email protected]",
|
| 946 |
+
"aff": "",
|
| 947 |
+
"aff_domain": "",
|
| 948 |
+
"position": "",
|
| 949 |
+
"rating": "",
|
| 950 |
+
"rating_avg": 0,
|
| 951 |
+
"project": "",
|
| 952 |
+
"github": ""
|
| 953 |
+
},
|
| 954 |
+
{
|
| 955 |
+
"id": "qEV_E7oCrKqWT",
|
| 956 |
+
"title": "Zero-Shot Learning Through Cross-Modal Transfer",
|
| 957 |
+
"track": "main",
|
| 958 |
+
"status": "Oral Workshop",
|
| 959 |
+
"keywords": "",
|
| 960 |
+
"primary_area": "",
|
| 961 |
+
"author": "Richard Socher;Milind Ganjoo;Hamsa Sridhar;Osbert Bastani;Christopher Manning;Andrew Y. Ng",
|
| 962 | |
| 963 |
+
"aff": "",
|
| 964 |
+
"aff_domain": "",
|
| 965 |
+
"position": "",
|
| 966 |
+
"rating": "",
|
| 967 |
+
"rating_avg": 0,
|
| 968 |
+
"project": "",
|
| 969 |
+
"github": ""
|
| 970 |
+
},
|
| 971 |
+
{
|
| 972 |
+
"id": "rOvg47Txgprkn",
|
| 973 |
+
"title": "Learnable Pooling Regions for Image Classification",
|
| 974 |
+
"track": "main",
|
| 975 |
+
"status": "Poster Workshop",
|
| 976 |
+
"keywords": "",
|
| 977 |
+
"primary_area": "",
|
| 978 |
+
"author": "Mateusz Malinowski;Mario Fritz",
|
| 979 |
+
"authorids": "[email protected];[email protected]",
|
| 980 |
+
"aff": "",
|
| 981 |
+
"aff_domain": "",
|
| 982 |
+
"position": "",
|
| 983 |
+
"rating": "",
|
| 984 |
+
"rating_avg": 0,
|
| 985 |
+
"project": "",
|
| 986 |
+
"github": ""
|
| 987 |
+
},
|
| 988 |
+
{
|
| 989 |
+
"id": "rtGYtZ-ZKSMzk",
|
| 990 |
+
"title": "Tree structured sparse coding on cubes",
|
| 991 |
+
"track": "main",
|
| 992 |
+
"status": "Poster Workshop",
|
| 993 |
+
"keywords": "",
|
| 994 |
+
"primary_area": "",
|
| 995 |
+
"author": "Arthur Szlam",
|
| 996 |
+
"authorids": "[email protected]",
|
| 997 |
+
"aff": "",
|
| 998 |
+
"aff_domain": "",
|
| 999 |
+
"position": "",
|
| 1000 |
+
"rating": "",
|
| 1001 |
+
"rating_avg": 0,
|
| 1002 |
+
"project": "",
|
| 1003 |
+
"github": ""
|
| 1004 |
+
},
|
| 1005 |
+
{
|
| 1006 |
+
"id": "tFbuFKWX3MFC8",
|
| 1007 |
+
"title": "Training Neural Networks with Stochastic Hessian-Free Optimization",
|
| 1008 |
+
"track": "main",
|
| 1009 |
+
"status": "Poster",
|
| 1010 |
+
"keywords": "",
|
| 1011 |
+
"primary_area": "",
|
| 1012 |
+
"author": "Ryan Kiros",
|
| 1013 |
+
"authorids": "[email protected]",
|
| 1014 |
+
"aff": "",
|
| 1015 |
+
"aff_domain": "",
|
| 1016 |
+
"position": "",
|
| 1017 |
+
"rating": "",
|
| 1018 |
+
"rating_avg": 0,
|
| 1019 |
+
"project": "",
|
| 1020 |
+
"github": ""
|
| 1021 |
+
},
|
| 1022 |
+
{
|
| 1023 |
+
"id": "ttnAE7vaATtaK",
|
| 1024 |
+
"title": "Indoor Semantic Segmentation using depth information",
|
| 1025 |
+
"track": "main",
|
| 1026 |
+
"status": "Oral",
|
| 1027 |
+
"keywords": "",
|
| 1028 |
+
"primary_area": "",
|
| 1029 |
+
"author": "Camille Couprie;Clement Farabet;Laurent Najman;Yann LeCun",
|
| 1030 |
+
"authorids": "[email protected];[email protected];[email protected];[email protected]",
|
| 1031 |
+
"aff": "",
|
| 1032 |
+
"aff_domain": "",
|
| 1033 |
+
"position": "",
|
| 1034 |
+
"rating": "",
|
| 1035 |
+
"rating_avg": 0,
|
| 1036 |
+
"project": "",
|
| 1037 |
+
"github": ""
|
| 1038 |
+
},
|
| 1039 |
+
{
|
| 1040 |
+
"id": "ttxM6DQKghdOi",
|
| 1041 |
+
"title": "Discrete Restricted Boltzmann Machines",
|
| 1042 |
+
"track": "main",
|
| 1043 |
+
"status": "Oral",
|
| 1044 |
+
"keywords": "",
|
| 1045 |
+
"primary_area": "",
|
| 1046 |
+
"author": "Guido F. Montufar;Jason Morton",
|
| 1047 |
+
"authorids": "[email protected];[email protected]",
|
| 1048 |
+
"aff": "",
|
| 1049 |
+
"aff_domain": "",
|
| 1050 |
+
"position": "",
|
| 1051 |
+
"rating": "",
|
| 1052 |
+
"rating_avg": 0,
|
| 1053 |
+
"project": "",
|
| 1054 |
+
"github": ""
|
| 1055 |
+
},
|
| 1056 |
+
{
|
| 1057 |
+
"id": "yGgjGkkbeFSbt",
|
| 1058 |
+
"title": "Saturating Auto-Encoder",
|
| 1059 |
+
"track": "main",
|
| 1060 |
+
"status": "Poster",
|
| 1061 |
+
"keywords": "",
|
| 1062 |
+
"primary_area": "",
|
| 1063 |
+
"author": "Ross Goroshin;Yann LeCun",
|
| 1064 |
+
"authorids": "[email protected];[email protected]",
|
| 1065 |
+
"aff": "",
|
| 1066 |
+
"aff_domain": "",
|
| 1067 |
+
"position": "",
|
| 1068 |
+
"rating": "",
|
| 1069 |
+
"rating_avg": 0,
|
| 1070 |
+
"project": "",
|
| 1071 |
+
"github": ""
|
| 1072 |
+
},
|
| 1073 |
+
{
|
| 1074 |
+
"id": "yyC_7RZTkUD5-",
|
| 1075 |
+
"title": "Deep Predictive Coding Networks",
|
| 1076 |
+
"track": "main",
|
| 1077 |
+
"status": "Poster Workshop",
|
| 1078 |
+
"keywords": "",
|
| 1079 |
+
"primary_area": "",
|
| 1080 |
+
"author": "Rakesh Chalasani;Jose C. Principe",
|
| 1081 |
+
"authorids": "[email protected];[email protected]",
|
| 1082 |
+
"aff": "",
|
| 1083 |
+
"aff_domain": "",
|
| 1084 |
+
"position": "",
|
| 1085 |
+
"rating": "",
|
| 1086 |
+
"rating_avg": 0,
|
| 1087 |
+
"project": "",
|
| 1088 |
+
"github": ""
|
| 1089 |
+
},
|
| 1090 |
+
{
|
| 1091 |
+
"id": "zzEf5eKLmAG0o",
|
| 1092 |
+
"title": "Learning Features with Structure-Adapting Multi-view Exponential Family Harmoniums",
|
| 1093 |
+
"track": "main",
|
| 1094 |
+
"status": "Poster Workshop",
|
| 1095 |
+
"keywords": "",
|
| 1096 |
+
"primary_area": "",
|
| 1097 |
+
"author": "YoonSeop Kang;Seungjin Choi",
|
| 1098 |
+
"authorids": "[email protected];[email protected]",
|
| 1099 |
+
"aff": "",
|
| 1100 |
+
"aff_domain": "",
|
| 1101 |
+
"position": "",
|
| 1102 |
+
"rating": "",
|
| 1103 |
+
"rating_avg": 0,
|
| 1104 |
+
"project": "",
|
| 1105 |
+
"github": ""
|
| 1106 |
+
},
|
| 1107 |
+
{
|
| 1108 |
+
"id": "zzKhQhsTYlzAZ",
|
| 1109 |
+
"title": "Regularized Discriminant Embedding for Visual Descriptor Learning",
|
| 1110 |
+
"track": "main",
|
| 1111 |
+
"status": "Poster Workshop",
|
| 1112 |
+
"keywords": "",
|
| 1113 |
+
"primary_area": "",
|
| 1114 |
+
"author": "Kye-Hyeon Kim;Rui Cai;Lei Zhang;Seungjin Choi",
|
| 1115 |
+
"authorids": "[email protected];[email protected];[email protected];[email protected]",
|
| 1116 |
+
"aff": "",
|
| 1117 |
+
"aff_domain": "",
|
| 1118 |
+
"position": "",
|
| 1119 |
+
"rating": "",
|
| 1120 |
+
"rating_avg": 0,
|
| 1121 |
+
"project": "",
|
| 1122 |
+
"github": ""
|
| 1123 |
+
},
|
| 1124 |
+
{
|
| 1125 |
+
"id": "zzy0H3ZbWiHsS",
|
| 1126 |
+
"title": "Audio Artist Identification by Deep Neural Network",
|
| 1127 |
+
"track": "main",
|
| 1128 |
+
"status": "Reject",
|
| 1129 |
+
"keywords": "",
|
| 1130 |
+
"primary_area": "",
|
| 1131 |
+
"author": "\u80e1\u632f;Kun Fu;Changshui Zhang",
|
| 1132 |
+
"authorids": "[email protected];Tsinghua Univ.;Tsinghua Univ.",
|
| 1133 |
+
"aff": "",
|
| 1134 |
+
"aff_domain": "",
|
| 1135 |
+
"position": "",
|
| 1136 |
+
"rating": "",
|
| 1137 |
+
"rating_avg": 0,
|
| 1138 |
+
"project": "",
|
| 1139 |
+
"github": ""
|
| 1140 |
+
}
|
| 1141 |
+
]
|
iclr/iclr2014.json
ADDED
|
@@ -0,0 +1,1175 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
[
|
| 2 |
+
{
|
| 3 |
+
"id": "-_FVMKvxVCQo1",
|
| 4 |
+
"title": "The return of AdaBoost.MH: multi-class Hamming trees",
|
| 5 |
+
"track": "main",
|
| 6 |
+
"status": "Poster",
|
| 7 |
+
"keywords": "",
|
| 8 |
+
"primary_area": "",
|
| 9 |
+
"author": "Bal\u00e1zs K\u00e9gl",
|
| 10 |
+
"authorids": "[email protected]",
|
| 11 |
+
"aff": "",
|
| 12 |
+
"aff_domain": "",
|
| 13 |
+
"position": "",
|
| 14 |
+
"rating": "",
|
| 15 |
+
"rating_avg": 0,
|
| 16 |
+
"project": "",
|
| 17 |
+
"github": ""
|
| 18 |
+
},
|
| 19 |
+
{
|
| 20 |
+
"id": "00Rp6XTNJq0GY",
|
| 21 |
+
"title": "Adaptive Feature Ranking for Unsupervised Transfer Learning",
|
| 22 |
+
"track": "main",
|
| 23 |
+
"status": "Poster",
|
| 24 |
+
"keywords": "",
|
| 25 |
+
"primary_area": "",
|
| 26 |
+
"author": "Son N. Tran;Artur d'Avila Garcez",
|
| 27 |
+
"authorids": "[email protected];[email protected]",
|
| 28 |
+
"aff": "",
|
| 29 |
+
"aff_domain": "",
|
| 30 |
+
"position": "",
|
| 31 |
+
"rating": "",
|
| 32 |
+
"rating_avg": 0,
|
| 33 |
+
"project": "",
|
| 34 |
+
"github": ""
|
| 35 |
+
},
|
| 36 |
+
{
|
| 37 |
+
"id": "26CF62DAFs2-K",
|
| 38 |
+
"title": "Learning Type-Driven Tensor-Based Meaning Representations",
|
| 39 |
+
"track": "main",
|
| 40 |
+
"status": "Poster",
|
| 41 |
+
"keywords": "",
|
| 42 |
+
"primary_area": "",
|
| 43 |
+
"author": "Tamara Polajnar;Luana Fagarasan;Stephen Clark",
|
| 44 |
+
"authorids": "[email protected];[email protected];[email protected]",
|
| 45 |
+
"aff": "",
|
| 46 |
+
"aff_domain": "",
|
| 47 |
+
"position": "",
|
| 48 |
+
"rating": "",
|
| 49 |
+
"rating_avg": 0,
|
| 50 |
+
"project": "",
|
| 51 |
+
"github": ""
|
| 52 |
+
},
|
| 53 |
+
{
|
| 54 |
+
"id": "33X9fd2-9FyZd",
|
| 55 |
+
"title": "Auto-Encoding Variational Bayes",
|
| 56 |
+
"track": "main",
|
| 57 |
+
"status": "Poster",
|
| 58 |
+
"keywords": "",
|
| 59 |
+
"primary_area": "",
|
| 60 |
+
"author": "Diederik P. Kingma;Max Welling",
|
| 61 |
+
"authorids": "[email protected];[email protected]",
|
| 62 |
+
"aff": "",
|
| 63 |
+
"aff_domain": "",
|
| 64 |
+
"position": "",
|
| 65 |
+
"rating": "",
|
| 66 |
+
"rating_avg": 0,
|
| 67 |
+
"project": "",
|
| 68 |
+
"github": ""
|
| 69 |
+
},
|
| 70 |
+
{
|
| 71 |
+
"id": "3RMnfrH_Fi8eU",
|
| 72 |
+
"title": "Fast Training of Convolutional Networks through FFTs",
|
| 73 |
+
"track": "main",
|
| 74 |
+
"status": "Poster",
|
| 75 |
+
"keywords": "",
|
| 76 |
+
"primary_area": "",
|
| 77 |
+
"author": "Michael Mathieu;Mikael Henaff;Yann LeCun",
|
| 78 |
+
"authorids": "[email protected];[email protected];[email protected]",
|
| 79 |
+
"aff": "",
|
| 80 |
+
"aff_domain": "",
|
| 81 |
+
"position": "",
|
| 82 |
+
"rating": "",
|
| 83 |
+
"rating_avg": 0,
|
| 84 |
+
"project": "",
|
| 85 |
+
"github": ""
|
| 86 |
+
},
|
| 87 |
+
{
|
| 88 |
+
"id": "4diyarNwq84_Q",
|
| 89 |
+
"title": "Can recursive neural tensor networks learn logical reasoning?",
|
| 90 |
+
"track": "main",
|
| 91 |
+
"status": "Poster",
|
| 92 |
+
"keywords": "",
|
| 93 |
+
"primary_area": "",
|
| 94 |
+
"author": "Samuel R. Bowman",
|
| 95 |
+
"authorids": "[email protected]",
|
| 96 |
+
"aff": "",
|
| 97 |
+
"aff_domain": "",
|
| 98 |
+
"position": "",
|
| 99 |
+
"rating": "",
|
| 100 |
+
"rating_avg": 0,
|
| 101 |
+
"project": "",
|
| 102 |
+
"github": ""
|
| 103 |
+
},
|
| 104 |
+
{
|
| 105 |
+
"id": "6rEnMF1okeiBO",
|
| 106 |
+
"title": "Low-Rank Approximations for Conditional Feedforward Computation in Deep Neural Networks",
|
| 107 |
+
"track": "main",
|
| 108 |
+
"status": "Poster",
|
| 109 |
+
"keywords": "",
|
| 110 |
+
"primary_area": "",
|
| 111 |
+
"author": "Andrew Davis;Itamar Arel",
|
| 112 |
+
"authorids": "[email protected];[email protected]",
|
| 113 |
+
"aff": "",
|
| 114 |
+
"aff_domain": "",
|
| 115 |
+
"position": "",
|
| 116 |
+
"rating": "",
|
| 117 |
+
"rating_avg": 0,
|
| 118 |
+
"project": "",
|
| 119 |
+
"github": ""
|
| 120 |
+
},
|
| 121 |
+
{
|
| 122 |
+
"id": "7Y52YHDS2X7ae",
|
| 123 |
+
"title": "Zero-Shot Learning by Convex Combination of Semantic Embeddings",
|
| 124 |
+
"track": "main",
|
| 125 |
+
"status": "Poster",
|
| 126 |
+
"keywords": "",
|
| 127 |
+
"primary_area": "",
|
| 128 |
+
"author": "Tomas Mikolov;Andrea Frome;Samy Bengio;Jonathon Shlens;Yoram Singer;Greg S. Corrado;Jeffrey Dean;Mohammad Norouzi",
|
| 129 | |
| 130 |
+
"aff": "",
|
| 131 |
+
"aff_domain": "",
|
| 132 |
+
"position": "",
|
| 133 |
+
"rating": "",
|
| 134 |
+
"rating_avg": 0,
|
| 135 |
+
"project": "",
|
| 136 |
+
"github": ""
|
| 137 |
+
},
|
| 138 |
+
{
|
| 139 |
+
"id": "8G-o3Hm_Z43Cf",
|
| 140 |
+
"title": "Learning Transformations for Classification Forests",
|
| 141 |
+
"track": "main",
|
| 142 |
+
"status": "Poster",
|
| 143 |
+
"keywords": "",
|
| 144 |
+
"primary_area": "",
|
| 145 |
+
"author": "Qiang Qiu;Guillermo Sapiro",
|
| 146 |
+
"authorids": "[email protected];[email protected]",
|
| 147 |
+
"aff": "",
|
| 148 |
+
"aff_domain": "",
|
| 149 |
+
"position": "",
|
| 150 |
+
"rating": "",
|
| 151 |
+
"rating_avg": 0,
|
| 152 |
+
"project": "",
|
| 153 |
+
"github": ""
|
| 154 |
+
},
|
| 155 |
+
{
|
| 156 |
+
"id": "8KokDTctkA8e4",
|
| 157 |
+
"title": "Learning generative models with visual attention",
|
| 158 |
+
"track": "main",
|
| 159 |
+
"status": "Poster",
|
| 160 |
+
"keywords": "",
|
| 161 |
+
"primary_area": "",
|
| 162 |
+
"author": "Charlie Tang;Nitish Srivastava;Ruslan Salakhutdinov",
|
| 163 |
+
"authorids": "[email protected];[email protected];[email protected]",
|
| 164 |
+
"aff": "",
|
| 165 |
+
"aff_domain": "",
|
| 166 |
+
"position": "",
|
| 167 |
+
"rating": "",
|
| 168 |
+
"rating_avg": 0,
|
| 169 |
+
"project": "",
|
| 170 |
+
"github": ""
|
| 171 |
+
},
|
| 172 |
+
{
|
| 173 |
+
"id": "AY3Hz-ujSEXUl",
|
| 174 |
+
"title": "Deep Belief Networks for Image Denoising",
|
| 175 |
+
"track": "main",
|
| 176 |
+
"status": "Poster",
|
| 177 |
+
"keywords": "",
|
| 178 |
+
"primary_area": "",
|
| 179 |
+
"author": "Mohammad Ali Keyvanrad;mohammad pezeshki;Mohammad Mehdi Homayounpour",
|
| 180 |
+
"authorids": "[email protected];[email protected];[email protected]",
|
| 181 |
+
"aff": "",
|
| 182 |
+
"aff_domain": "",
|
| 183 |
+
"position": "",
|
| 184 |
+
"rating": "",
|
| 185 |
+
"rating_avg": 0,
|
| 186 |
+
"project": "",
|
| 187 |
+
"github": ""
|
| 188 |
+
},
|
| 189 |
+
{
|
| 190 |
+
"id": "BBxkB2w0I_OjZ",
|
| 191 |
+
"title": "Multi-digit Number Recognition from Street View Imagery using Deep Convolutional Neural Networks",
|
| 192 |
+
"track": "main",
|
| 193 |
+
"status": "Poster",
|
| 194 |
+
"keywords": "",
|
| 195 |
+
"primary_area": "",
|
| 196 |
+
"author": "Julian Ibarz;Ian Goodfellow;Sacha Arnoud;Vinay Shet;Yaroslav Bulatov",
|
| 197 |
+
"authorids": "[email protected];[email protected];[email protected];[email protected];[email protected]",
|
| 198 |
+
"aff": "",
|
| 199 |
+
"aff_domain": "",
|
| 200 |
+
"position": "",
|
| 201 |
+
"rating": "",
|
| 202 |
+
"rating_avg": 0,
|
| 203 |
+
"project": "",
|
| 204 |
+
"github": ""
|
| 205 |
+
},
|
| 206 |
+
{
|
| 207 |
+
"id": "BId1QQRE1gQLZ",
|
| 208 |
+
"title": "Multi-View Priors for Learning Detectors from Sparse Viewpoint Data",
|
| 209 |
+
"track": "main",
|
| 210 |
+
"status": "Poster",
|
| 211 |
+
"keywords": "",
|
| 212 |
+
"primary_area": "",
|
| 213 |
+
"author": "Bojan Pepik;Michael Stark;Peter Gehler;Bernt Schiele",
|
| 214 |
+
"authorids": "[email protected];[email protected];[email protected];[email protected]",
|
| 215 |
+
"aff": "",
|
| 216 |
+
"aff_domain": "",
|
| 217 |
+
"position": "",
|
| 218 |
+
"rating": "",
|
| 219 |
+
"rating_avg": 0,
|
| 220 |
+
"project": "",
|
| 221 |
+
"github": ""
|
| 222 |
+
},
|
| 223 |
+
{
|
| 224 |
+
"id": "CRge-EDLedRUr",
|
| 225 |
+
"title": "Efficient Visual Coding: From Retina To V2",
|
| 226 |
+
"track": "main",
|
| 227 |
+
"status": "Poster",
|
| 228 |
+
"keywords": "",
|
| 229 |
+
"primary_area": "",
|
| 230 |
+
"author": "Honghao Shan;Garrison Cottrell",
|
| 231 |
+
"authorids": "[email protected];[email protected]",
|
| 232 |
+
"aff": "",
|
| 233 |
+
"aff_domain": "",
|
| 234 |
+
"position": "",
|
| 235 |
+
"rating": "",
|
| 236 |
+
"rating_avg": 0,
|
| 237 |
+
"project": "",
|
| 238 |
+
"github": ""
|
| 239 |
+
},
|
| 240 |
+
{
|
| 241 |
+
"id": "DETu4zMyQH4kV",
|
| 242 |
+
"title": "Semistochastic Quadratic Bound Methods",
|
| 243 |
+
"track": "main",
|
| 244 |
+
"status": "Poster",
|
| 245 |
+
"keywords": "",
|
| 246 |
+
"primary_area": "",
|
| 247 |
+
"author": "Aleksandr Y. Aravkin;Anna Choromanska;Tony Jebara;Dimitri Kanevsky",
|
| 248 |
+
"authorids": "[email protected];[email protected];[email protected];[email protected]",
|
| 249 |
+
"aff": "",
|
| 250 |
+
"aff_domain": "",
|
| 251 |
+
"position": "",
|
| 252 |
+
"rating": "",
|
| 253 |
+
"rating_avg": 0,
|
| 254 |
+
"project": "",
|
| 255 |
+
"github": ""
|
| 256 |
+
},
|
| 257 |
+
{
|
| 258 |
+
"id": "DQNsQf-UsoDBa",
|
| 259 |
+
"title": "Spectral Networks and Locally Connected Networks on Graphs",
|
| 260 |
+
"track": "main",
|
| 261 |
+
"status": "Poster",
|
| 262 |
+
"keywords": "",
|
| 263 |
+
"primary_area": "",
|
| 264 |
+
"author": "Joan Bruna;Wojciech Zaremba;Arthur Szlam;Yann LeCun",
|
| 265 |
+
"authorids": "[email protected];[email protected];[email protected];[email protected]",
|
| 266 |
+
"aff": "",
|
| 267 |
+
"aff_domain": "",
|
| 268 |
+
"position": "",
|
| 269 |
+
"rating": "",
|
| 270 |
+
"rating_avg": 0,
|
| 271 |
+
"project": "",
|
| 272 |
+
"github": ""
|
| 273 |
+
},
|
| 274 |
+
{
|
| 275 |
+
"id": "DnsBnbl6TQD6t",
|
| 276 |
+
"title": "Learning High-level Image Representation for Image Retrieval via Multi-Task DNN using Clickthrough Data",
|
| 277 |
+
"track": "main",
|
| 278 |
+
"status": "Poster",
|
| 279 |
+
"keywords": "",
|
| 280 |
+
"primary_area": "",
|
| 281 |
+
"author": "Wei-Ying Ma;Tiejun Zhao;Kuiyuan Yang;Wei Yu;Yalong Bai",
|
| 282 |
+
"authorids": "[email protected];[email protected];[email protected];[email protected];[email protected]",
|
| 283 |
+
"aff": "",
|
| 284 |
+
"aff_domain": "",
|
| 285 |
+
"position": "",
|
| 286 |
+
"rating": "",
|
| 287 |
+
"rating_avg": 0,
|
| 288 |
+
"project": "",
|
| 289 |
+
"github": ""
|
| 290 |
+
},
|
| 291 |
+
{
|
| 292 |
+
"id": "EXqiEZhNias13",
|
| 293 |
+
"title": "Continuous Learning: Engineering Super Features With Feature Algebras",
|
| 294 |
+
"track": "main",
|
| 295 |
+
"status": "Poster",
|
| 296 |
+
"keywords": "",
|
| 297 |
+
"primary_area": "",
|
| 298 |
+
"author": "Michael Tetelman",
|
| 299 |
+
"authorids": "[email protected]",
|
| 300 |
+
"aff": "",
|
| 301 |
+
"aff_domain": "",
|
| 302 |
+
"position": "",
|
| 303 |
+
"rating": "",
|
| 304 |
+
"rating_avg": 0,
|
| 305 |
+
"project": "",
|
| 306 |
+
"github": ""
|
| 307 |
+
},
|
| 308 |
+
{
|
| 309 |
+
"id": "HH-uZ8U2O1aWf",
|
| 310 |
+
"title": "Deep and Wide Multiscale Recursive Networks for Robust Image Labeling",
|
| 311 |
+
"track": "main",
|
| 312 |
+
"status": "Poster",
|
| 313 |
+
"keywords": "",
|
| 314 |
+
"primary_area": "",
|
| 315 |
+
"author": "Gary B. Huang;Viren Jain",
|
| 316 |
+
"authorids": "[email protected];[email protected]",
|
| 317 |
+
"aff": "",
|
| 318 |
+
"aff_domain": "",
|
| 319 |
+
"position": "",
|
| 320 |
+
"rating": "",
|
| 321 |
+
"rating_avg": 0,
|
| 322 |
+
"project": "",
|
| 323 |
+
"github": ""
|
| 324 |
+
},
|
| 325 |
+
{
|
| 326 |
+
"id": "Hq5MgBFOP62-X",
|
| 327 |
+
"title": "OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networks",
|
| 328 |
+
"track": "main",
|
| 329 |
+
"status": "Poster",
|
| 330 |
+
"keywords": "",
|
| 331 |
+
"primary_area": "",
|
| 332 |
+
"author": "Michael Mathieu;Yann LeCun;Rob Fergus;David Eigen;Pierre Sermanet;Xiang Zhang",
|
| 333 | |
| 334 |
+
"aff": "",
|
| 335 |
+
"aff_domain": "",
|
| 336 |
+
"position": "",
|
| 337 |
+
"rating": "",
|
| 338 |
+
"rating_avg": 0,
|
| 339 |
+
"project": "",
|
| 340 |
+
"github": ""
|
| 341 |
+
},
|
| 342 |
+
{
|
| 343 |
+
"id": "II-mIcAshLID0",
|
| 344 |
+
"title": "Stopping Criteria in Contrastive Divergence: Alternatives to the Reconstruction Error",
|
| 345 |
+
"track": "main",
|
| 346 |
+
"status": "Poster",
|
| 347 |
+
"keywords": "",
|
| 348 |
+
"primary_area": "",
|
| 349 |
+
"author": "David Buchaca;Enrique Romero;Ferran Mazzanti;Jordi Delgado",
|
| 350 |
+
"authorids": "[email protected];[email protected];[email protected];[email protected]",
|
| 351 |
+
"aff": "",
|
| 352 |
+
"aff_domain": "",
|
| 353 |
+
"position": "",
|
| 354 |
+
"rating": "",
|
| 355 |
+
"rating_avg": 0,
|
| 356 |
+
"project": "",
|
| 357 |
+
"github": ""
|
| 358 |
+
},
|
| 359 |
+
{
|
| 360 |
+
"id": "IrVvIL2BaXrg4",
|
| 361 |
+
"title": "Reference Distance Estimator",
|
| 362 |
+
"track": "main",
|
| 363 |
+
"status": "Poster",
|
| 364 |
+
"keywords": "",
|
| 365 |
+
"primary_area": "",
|
| 366 |
+
"author": "Yanpeng Li",
|
| 367 |
+
"authorids": "[email protected]",
|
| 368 |
+
"aff": "",
|
| 369 |
+
"aff_domain": "",
|
| 370 |
+
"position": "",
|
| 371 |
+
"rating": "",
|
| 372 |
+
"rating_avg": 0,
|
| 373 |
+
"project": "",
|
| 374 |
+
"github": ""
|
| 375 |
+
},
|
| 376 |
+
{
|
| 377 |
+
"id": "L80PLIixPIXTH",
|
| 378 |
+
"title": "How to Construct Deep Recurrent Neural Networks",
|
| 379 |
+
"track": "main",
|
| 380 |
+
"status": "Poster",
|
| 381 |
+
"keywords": "",
|
| 382 |
+
"primary_area": "",
|
| 383 |
+
"author": "Razvan Pascanu;Caglar Gulcehre;KyungHyun Cho;Yoshua Bengio",
|
| 384 |
+
"authorids": "[email protected];[email protected];[email protected];[email protected]",
|
| 385 |
+
"aff": "",
|
| 386 |
+
"aff_domain": "",
|
| 387 |
+
"position": "",
|
| 388 |
+
"rating": "",
|
| 389 |
+
"rating_avg": 0,
|
| 390 |
+
"project": "",
|
| 391 |
+
"github": ""
|
| 392 |
+
},
|
| 393 |
+
{
|
| 394 |
+
"id": "LwyBkw8Nh6Y1J",
|
| 395 |
+
"title": "Unit Tests for Stochastic Optimization",
|
| 396 |
+
"track": "main",
|
| 397 |
+
"status": "Poster",
|
| 398 |
+
"keywords": "",
|
| 399 |
+
"primary_area": "",
|
| 400 |
+
"author": "Tom Schaul;Ioannis Antonoglou;David Silver",
|
| 401 |
+
"authorids": "[email protected];[email protected];[email protected]",
|
| 402 |
+
"aff": "",
|
| 403 |
+
"aff_domain": "",
|
| 404 |
+
"position": "",
|
| 405 |
+
"rating": "",
|
| 406 |
+
"rating_avg": 0,
|
| 407 |
+
"project": "",
|
| 408 |
+
"github": ""
|
| 409 |
+
},
|
| 410 |
+
{
|
| 411 |
+
"id": "M7uvMK0-IZCh9",
|
| 412 |
+
"title": "Image Representation Learning Using Graph Regularized Auto-Encoders",
|
| 413 |
+
"track": "main",
|
| 414 |
+
"status": "Poster",
|
| 415 |
+
"keywords": "",
|
| 416 |
+
"primary_area": "",
|
| 417 |
+
"author": "Yiyi Liao;Yue Wang;Yong Liu",
|
| 418 |
+
"authorids": "[email protected];[email protected];[email protected]",
|
| 419 |
+
"aff": "",
|
| 420 |
+
"aff_domain": "",
|
| 421 |
+
"position": "",
|
| 422 |
+
"rating": "",
|
| 423 |
+
"rating_avg": 0,
|
| 424 |
+
"project": "",
|
| 425 |
+
"github": ""
|
| 426 |
+
},
|
| 427 |
+
{
|
| 428 |
+
"id": "MMG-yUjRFZqpn",
|
| 429 |
+
"title": "A Simple Model for Learning Multilingual Compositional Semantics",
|
| 430 |
+
"track": "main",
|
| 431 |
+
"status": "Poster",
|
| 432 |
+
"keywords": "",
|
| 433 |
+
"primary_area": "",
|
| 434 |
+
"author": "Karl Moritz Hermann;Phil Blunsom",
|
| 435 |
+
"authorids": "[email protected];[email protected]",
|
| 436 |
+
"aff": "",
|
| 437 |
+
"aff_domain": "",
|
| 438 |
+
"position": "",
|
| 439 |
+
"rating": "",
|
| 440 |
+
"rating_avg": 0,
|
| 441 |
+
"project": "",
|
| 442 |
+
"github": ""
|
| 443 |
+
},
|
| 444 |
+
{
|
| 445 |
+
"id": "MMSzYHL_g1V83",
|
| 446 |
+
"title": "Rate-Distortion Auto-Encoders",
|
| 447 |
+
"track": "main",
|
| 448 |
+
"status": "Poster",
|
| 449 |
+
"keywords": "",
|
| 450 |
+
"primary_area": "",
|
| 451 |
+
"author": "Luis G. Sanchez Giraldo;Jose C. Principe",
|
| 452 |
+
"authorids": "[email protected];[email protected]",
|
| 453 |
+
"aff": "",
|
| 454 |
+
"aff_domain": "",
|
| 455 |
+
"position": "",
|
| 456 |
+
"rating": "",
|
| 457 |
+
"rating_avg": 0,
|
| 458 |
+
"project": "",
|
| 459 |
+
"github": ""
|
| 460 |
+
},
|
| 461 |
+
{
|
| 462 |
+
"id": "NNP_NfOK_ENK4",
|
| 463 |
+
"title": "An Architecture for Distinguishing between Predictors and Inhibitors in Reinforcement Learning",
|
| 464 |
+
"track": "main",
|
| 465 |
+
"status": "Poster",
|
| 466 |
+
"keywords": "",
|
| 467 |
+
"primary_area": "",
|
| 468 |
+
"author": "Patrick C. Connor;Thomas P. Trappenberg",
|
| 469 |
+
"authorids": "[email protected];[email protected]",
|
| 470 |
+
"aff": "",
|
| 471 |
+
"aff_domain": "",
|
| 472 |
+
"position": "",
|
| 473 |
+
"rating": "",
|
| 474 |
+
"rating_avg": 0,
|
| 475 |
+
"project": "",
|
| 476 |
+
"github": ""
|
| 477 |
+
},
|
| 478 |
+
{
|
| 479 |
+
"id": "NPFdalK3djNuI",
|
| 480 |
+
"title": "A Generative Product-of-Filters Model of Audio",
|
| 481 |
+
"track": "main",
|
| 482 |
+
"status": "Poster",
|
| 483 |
+
"keywords": "",
|
| 484 |
+
"primary_area": "",
|
| 485 |
+
"author": "Dawen Liang;Mathew D. Hoffman;Gautham Mysore",
|
| 486 |
+
"authorids": "[email protected];[email protected];[email protected]",
|
| 487 |
+
"aff": "",
|
| 488 |
+
"aff_domain": "",
|
| 489 |
+
"position": "",
|
| 490 |
+
"rating": "",
|
| 491 |
+
"rating_avg": 0,
|
| 492 |
+
"project": "",
|
| 493 |
+
"github": ""
|
| 494 |
+
},
|
| 495 |
+
{
|
| 496 |
+
"id": "NR4KjDE0w9RXD",
|
| 497 |
+
"title": "Improving Deep Neural Networks with Probabilistic Maxout Units",
|
| 498 |
+
"track": "main",
|
| 499 |
+
"status": "Poster",
|
| 500 |
+
"keywords": "",
|
| 501 |
+
"primary_area": "",
|
| 502 |
+
"author": "Jost Tobias Springenberg;Martin Riedmiller",
|
| 503 |
+
"authorids": "[email protected];[email protected]",
|
| 504 |
+
"aff": "",
|
| 505 |
+
"aff_domain": "",
|
| 506 |
+
"position": "",
|
| 507 |
+
"rating": "",
|
| 508 |
+
"rating_avg": 0,
|
| 509 |
+
"project": "",
|
| 510 |
+
"github": ""
|
| 511 |
+
},
|
| 512 |
+
{
|
| 513 |
+
"id": "OP4ePyQXNu-da",
|
| 514 |
+
"title": "On Fast Dropout and its Applicability to Recurrent Networks",
|
| 515 |
+
"track": "main",
|
| 516 |
+
"status": "Poster",
|
| 517 |
+
"keywords": "",
|
| 518 |
+
"primary_area": "",
|
| 519 |
+
"author": "Justin Bayer;Christian Osendorfer;Sebastian Urban;Nutan Chen;Daniela Korhammer;Patrick van der Smagt",
|
| 520 | |
| 521 |
+
"aff": "",
|
| 522 |
+
"aff_domain": "",
|
| 523 |
+
"position": "",
|
| 524 |
+
"rating": "",
|
| 525 |
+
"rating_avg": 0,
|
| 526 |
+
"project": "",
|
| 527 |
+
"github": ""
|
| 528 |
+
},
|
| 529 |
+
{
|
| 530 |
+
"id": "O_cyOSWv8TrlS",
|
| 531 |
+
"title": "Neuronal Synchrony in Complex-Valued Deep Networks",
|
| 532 |
+
"track": "main",
|
| 533 |
+
"status": "Poster",
|
| 534 |
+
"keywords": "",
|
| 535 |
+
"primary_area": "",
|
| 536 |
+
"author": "David Reichert;Thomas Serre",
|
| 537 |
+
"authorids": "[email protected];[email protected]",
|
| 538 |
+
"aff": "",
|
| 539 |
+
"aff_domain": "",
|
| 540 |
+
"position": "",
|
| 541 |
+
"rating": "",
|
| 542 |
+
"rating_avg": 0,
|
| 543 |
+
"project": "",
|
| 544 |
+
"github": ""
|
| 545 |
+
},
|
| 546 |
+
{
|
| 547 |
+
"id": "PiMICQ7tbB-Aa",
|
| 548 |
+
"title": "Distinction between features extracted using deep belief networks",
|
| 549 |
+
"track": "main",
|
| 550 |
+
"status": "Poster",
|
| 551 |
+
"keywords": "",
|
| 552 |
+
"primary_area": "",
|
| 553 |
+
"author": "mohammad pezeshki;Sajjad Gholami;Ahmad Nickabadi",
|
| 554 |
+
"authorids": "[email protected];[email protected];[email protected]",
|
| 555 |
+
"aff": "",
|
| 556 |
+
"aff_domain": "",
|
| 557 |
+
"position": "",
|
| 558 |
+
"rating": "",
|
| 559 |
+
"rating_avg": 0,
|
| 560 |
+
"project": "",
|
| 561 |
+
"github": ""
|
| 562 |
+
},
|
| 563 |
+
{
|
| 564 |
+
"id": "PtRd6ZOVAm7Lv",
|
| 565 |
+
"title": "Sparse, complex-valued representations of natural sounds learned with phase and amplitude continuity priors",
|
| 566 |
+
"track": "main",
|
| 567 |
+
"status": "Poster",
|
| 568 |
+
"keywords": "",
|
| 569 |
+
"primary_area": "",
|
| 570 |
+
"author": "Wiktor Mlynarski",
|
| 571 |
+
"authorids": "[email protected]",
|
| 572 |
+
"aff": "",
|
| 573 |
+
"aff_domain": "",
|
| 574 |
+
"position": "",
|
| 575 |
+
"rating": "",
|
| 576 |
+
"rating_avg": 0,
|
| 577 |
+
"project": "",
|
| 578 |
+
"github": ""
|
| 579 |
+
},
|
| 580 |
+
{
|
| 581 |
+
"id": "QDm4QXNOsuQVE",
|
| 582 |
+
"title": "k-Sparse Autoencoders",
|
| 583 |
+
"track": "main",
|
| 584 |
+
"status": "Poster",
|
| 585 |
+
"keywords": "",
|
| 586 |
+
"primary_area": "",
|
| 587 |
+
"author": "Alireza Makhzani;Brendan Frey",
|
| 588 |
+
"authorids": "[email protected];[email protected]",
|
| 589 |
+
"aff": "",
|
| 590 |
+
"aff_domain": "",
|
| 591 |
+
"position": "",
|
| 592 |
+
"rating": "",
|
| 593 |
+
"rating_avg": 0,
|
| 594 |
+
"project": "",
|
| 595 |
+
"github": ""
|
| 596 |
+
},
|
| 597 |
+
{
|
| 598 |
+
"id": "R5x4IjeY4351N",
|
| 599 |
+
"title": "Why does the unsupervised pretraining encourage moderate-sparseness?",
|
| 600 |
+
"track": "main",
|
| 601 |
+
"status": "Poster",
|
| 602 |
+
"keywords": "",
|
| 603 |
+
"primary_area": "",
|
| 604 |
+
"author": "Jun Li;Wei Luo;Jian Yang;Xiaotong Yuan",
|
| 605 |
+
"authorids": "[email protected];[email protected];[email protected];[email protected]",
|
| 606 |
+
"aff": "",
|
| 607 |
+
"aff_domain": "",
|
| 608 |
+
"position": "",
|
| 609 |
+
"rating": "",
|
| 610 |
+
"rating_avg": 0,
|
| 611 |
+
"project": "",
|
| 612 |
+
"github": ""
|
| 613 |
+
},
|
| 614 |
+
{
|
| 615 |
+
"id": "UVH3Ucewd-IXZ",
|
| 616 |
+
"title": "Deep learning for neuroimaging: a validation study",
|
| 617 |
+
"track": "main",
|
| 618 |
+
"status": "Poster",
|
| 619 |
+
"keywords": "",
|
| 620 |
+
"primary_area": "",
|
| 621 |
+
"author": "Sergey M. Plis;Devon R. Hjelm;Ruslan Salakhutdinov;Vince D. Calhoun",
|
| 622 |
+
"authorids": "[email protected];[email protected];[email protected];[email protected]",
|
| 623 |
+
"aff": "",
|
| 624 |
+
"aff_domain": "",
|
| 625 |
+
"position": "",
|
| 626 |
+
"rating": "",
|
| 627 |
+
"rating_avg": 0,
|
| 628 |
+
"project": "",
|
| 629 |
+
"github": ""
|
| 630 |
+
},
|
| 631 |
+
{
|
| 632 |
+
"id": "UYmwU4C1wZi16",
|
| 633 |
+
"title": "Feature Graph Architectures",
|
| 634 |
+
"track": "main",
|
| 635 |
+
"status": "Poster",
|
| 636 |
+
"keywords": "",
|
| 637 |
+
"primary_area": "",
|
| 638 |
+
"author": "Richard Davis;Sanjay Chawla;Philip Leong",
|
| 639 |
+
"authorids": "[email protected];[email protected];[email protected]",
|
| 640 |
+
"aff": "",
|
| 641 |
+
"aff_domain": "",
|
| 642 |
+
"position": "",
|
| 643 |
+
"rating": "",
|
| 644 |
+
"rating_avg": 0,
|
| 645 |
+
"project": "",
|
| 646 |
+
"github": ""
|
| 647 |
+
},
|
| 648 |
+
{
|
| 649 |
+
"id": "Wi9tWlxh4Jwu6",
|
| 650 |
+
"title": "Understanding Deep Architectures using a Recursive Convolutional Network",
|
| 651 |
+
"track": "main",
|
| 652 |
+
"status": "Poster",
|
| 653 |
+
"keywords": "",
|
| 654 |
+
"primary_area": "",
|
| 655 |
+
"author": "David Eigen;Jason Rolfe;Rob Fergus;Yann LeCun",
|
| 656 |
+
"authorids": "[email protected];[email protected];[email protected];[email protected]",
|
| 657 |
+
"aff": "",
|
| 658 |
+
"aff_domain": "",
|
| 659 |
+
"position": "",
|
| 660 |
+
"rating": "",
|
| 661 |
+
"rating_avg": 0,
|
| 662 |
+
"project": "",
|
| 663 |
+
"github": ""
|
| 664 |
+
},
|
| 665 |
+
{
|
| 666 |
+
"id": "YDXrDdbom9YCi",
|
| 667 |
+
"title": "Large-scale Multi-label Text Classification - Revisiting Neural Networks",
|
| 668 |
+
"track": "main",
|
| 669 |
+
"status": "Poster",
|
| 670 |
+
"keywords": "",
|
| 671 |
+
"primary_area": "",
|
| 672 |
+
"author": "Jinseok Nam;Jungi Kim;Iryna Gurevych;Johannes F\u00fcrnkranz",
|
| 673 |
+
"authorids": "[email protected];[email protected];[email protected];[email protected]",
|
| 674 |
+
"aff": "",
|
| 675 |
+
"aff_domain": "",
|
| 676 |
+
"position": "",
|
| 677 |
+
"rating": "",
|
| 678 |
+
"rating_avg": 0,
|
| 679 |
+
"project": "",
|
| 680 |
+
"github": ""
|
| 681 |
+
},
|
| 682 |
+
{
|
| 683 |
+
"id": "YHGzHsybzQU0l",
|
| 684 |
+
"title": "Factorial Hidden Markov Models for Learning Representations of Natural Language",
|
| 685 |
+
"track": "main",
|
| 686 |
+
"status": "Poster",
|
| 687 |
+
"keywords": "",
|
| 688 |
+
"primary_area": "",
|
| 689 |
+
"author": "Anjan Nepal;Alexander Yates",
|
| 690 |
+
"authorids": "[email protected];[email protected]",
|
| 691 |
+
"aff": "",
|
| 692 |
+
"aff_domain": "",
|
| 693 |
+
"position": "",
|
| 694 |
+
"rating": "",
|
| 695 |
+
"rating_avg": 0,
|
| 696 |
+
"project": "",
|
| 697 |
+
"github": ""
|
| 698 |
+
},
|
| 699 |
+
{
|
| 700 |
+
"id": "YvgSX22hONWpI",
|
| 701 |
+
"title": "Multimodal Transitions for Generative Stochastic Networks",
|
| 702 |
+
"track": "main",
|
| 703 |
+
"status": "Poster",
|
| 704 |
+
"keywords": "",
|
| 705 |
+
"primary_area": "",
|
| 706 |
+
"author": "Sherjil Ozair;Li Yao;Yoshua Bengio",
|
| 707 |
+
"authorids": "[email protected];[email protected];[email protected]",
|
| 708 |
+
"aff": "",
|
| 709 |
+
"aff_domain": "",
|
| 710 |
+
"position": "",
|
| 711 |
+
"rating": "",
|
| 712 |
+
"rating_avg": 0,
|
| 713 |
+
"project": "",
|
| 714 |
+
"github": ""
|
| 715 |
+
},
|
| 716 |
+
{
|
| 717 |
+
"id": "ZZ7T6hXbaEcAQ",
|
| 718 |
+
"title": "An empirical analysis of dropout in piecewise linear networks",
|
| 719 |
+
"track": "main",
|
| 720 |
+
"status": "Poster",
|
| 721 |
+
"keywords": "",
|
| 722 |
+
"primary_area": "",
|
| 723 |
+
"author": "David Warde-Farley;Ian Goodfellow;Aaron Courville;Yoshua Bengio",
|
| 724 |
+
"authorids": "[email protected];[email protected];[email protected];[email protected]",
|
| 725 |
+
"aff": "",
|
| 726 |
+
"aff_domain": "",
|
| 727 |
+
"position": "",
|
| 728 |
+
"rating": "",
|
| 729 |
+
"rating_avg": 0,
|
| 730 |
+
"project": "",
|
| 731 |
+
"github": ""
|
| 732 |
+
},
|
| 733 |
+
{
|
| 734 |
+
"id": "__Jk_HAdtfK5W",
|
| 735 |
+
"title": "Learning to encode motion using spatio-temporal synchrony",
|
| 736 |
+
"track": "main",
|
| 737 |
+
"status": "Poster",
|
| 738 |
+
"keywords": "",
|
| 739 |
+
"primary_area": "",
|
| 740 |
+
"author": "Kishore Reddy Konda;Roland Memisevic;Vincent Michalski",
|
| 741 |
+
"authorids": "[email protected];[email protected];[email protected]",
|
| 742 |
+
"aff": "",
|
| 743 |
+
"aff_domain": "",
|
| 744 |
+
"position": "",
|
| 745 |
+
"rating": "",
|
| 746 |
+
"rating_avg": 0,
|
| 747 |
+
"project": "",
|
| 748 |
+
"github": ""
|
| 749 |
+
},
|
| 750 |
+
{
|
| 751 |
+
"id": "_wzZwKpTDF_9C",
|
| 752 |
+
"title": "Exact solutions to the nonlinear dynamics of learning in deep linear neural networks",
|
| 753 |
+
"track": "main",
|
| 754 |
+
"status": "Poster",
|
| 755 |
+
"keywords": "",
|
| 756 |
+
"primary_area": "",
|
| 757 |
+
"author": "Andrew Saxe;James L. McClelland;Surya Ganguli",
|
| 758 |
+
"authorids": "[email protected];[email protected];[email protected]",
|
| 759 |
+
"aff": "",
|
| 760 |
+
"aff_domain": "",
|
| 761 |
+
"position": "",
|
| 762 |
+
"rating": "",
|
| 763 |
+
"rating_avg": 0,
|
| 764 |
+
"project": "",
|
| 765 |
+
"github": ""
|
| 766 |
+
},
|
| 767 |
+
{
|
| 768 |
+
"id": "bSaT4mmQt84Lx",
|
| 769 |
+
"title": "On the number of inference regions of deep feed forward networks with piece-wise linear activations",
|
| 770 |
+
"track": "main",
|
| 771 |
+
"status": "Poster",
|
| 772 |
+
"keywords": "",
|
| 773 |
+
"primary_area": "",
|
| 774 |
+
"author": "Razvan Pascanu;Guido F. Montufar;Yoshua Bengio",
|
| 775 |
+
"authorids": "[email protected];[email protected];[email protected]",
|
| 776 |
+
"aff": "",
|
| 777 |
+
"aff_domain": "",
|
| 778 |
+
"position": "",
|
| 779 |
+
"rating": "",
|
| 780 |
+
"rating_avg": 0,
|
| 781 |
+
"project": "",
|
| 782 |
+
"github": ""
|
| 783 |
+
},
|
| 784 |
+
{
|
| 785 |
+
"id": "bb7SwHahSUpiq",
|
| 786 |
+
"title": "Approximated Infomax Early Stopping: Revisiting Gaussian RBMs on Natural Images",
|
| 787 |
+
"track": "main",
|
| 788 |
+
"status": "Poster",
|
| 789 |
+
"keywords": "",
|
| 790 |
+
"primary_area": "",
|
| 791 |
+
"author": "Taichi Kiwaki;Takaki Makino;Kazuyuki Aihara",
|
| 792 |
+
"authorids": "[email protected];[email protected];[email protected]",
|
| 793 |
+
"aff": "",
|
| 794 |
+
"aff_domain": "",
|
| 795 |
+
"position": "",
|
| 796 |
+
"rating": "",
|
| 797 |
+
"rating_avg": 0,
|
| 798 |
+
"project": "",
|
| 799 |
+
"github": ""
|
| 800 |
+
},
|
| 801 |
+
{
|
| 802 |
+
"id": "gg4nKrblw0gkf",
|
| 803 |
+
"title": "Bounding the Test Log-Likelihood of Generative Models",
|
| 804 |
+
"track": "main",
|
| 805 |
+
"status": "Poster",
|
| 806 |
+
"keywords": "",
|
| 807 |
+
"primary_area": "",
|
| 808 |
+
"author": "Yoshua Bengio;Li Yao;KyungHyun Cho",
|
| 809 |
+
"authorids": "[email protected];[email protected];[email protected]",
|
| 810 |
+
"aff": "",
|
| 811 |
+
"aff_domain": "",
|
| 812 |
+
"position": "",
|
| 813 |
+
"rating": "",
|
| 814 |
+
"rating_avg": 0,
|
| 815 |
+
"project": "",
|
| 816 |
+
"github": ""
|
| 817 |
+
},
|
| 818 |
+
{
|
| 819 |
+
"id": "kkUZ1FHlLaPAf",
|
| 820 |
+
"title": "Learning Paired-associate Images with An Unsupervised Deep Learning Architecture",
|
| 821 |
+
"track": "main",
|
| 822 |
+
"status": "Poster",
|
| 823 |
+
"keywords": "",
|
| 824 |
+
"primary_area": "",
|
| 825 |
+
"author": "Ti Wang;Daniel L. Silver",
|
| 826 |
+
"authorids": "[email protected];[email protected]",
|
| 827 |
+
"aff": "",
|
| 828 |
+
"aff_domain": "",
|
| 829 |
+
"position": "",
|
| 830 |
+
"rating": "",
|
| 831 |
+
"rating_avg": 0,
|
| 832 |
+
"project": "",
|
| 833 |
+
"github": ""
|
| 834 |
+
},
|
| 835 |
+
{
|
| 836 |
+
"id": "kkgljR8O6hjHA",
|
| 837 |
+
"title": "EXMOVES: Classifier-based Features for Scalable Action Recognition",
|
| 838 |
+
"track": "main",
|
| 839 |
+
"status": "Poster",
|
| 840 |
+
"keywords": "",
|
| 841 |
+
"primary_area": "",
|
| 842 |
+
"author": "Du Tran;Lorenzo Torresani",
|
| 843 |
+
"authorids": "[email protected];[email protected]",
|
| 844 |
+
"aff": "",
|
| 845 |
+
"aff_domain": "",
|
| 846 |
+
"position": "",
|
| 847 |
+
"rating": "",
|
| 848 |
+
"rating_avg": 0,
|
| 849 |
+
"project": "",
|
| 850 |
+
"github": ""
|
| 851 |
+
},
|
| 852 |
+
{
|
| 853 |
+
"id": "kklr_MTHMRQjG",
|
| 854 |
+
"title": "Intriguing properties of neural networks",
|
| 855 |
+
"track": "main",
|
| 856 |
+
"status": "Poster",
|
| 857 |
+
"keywords": "",
|
| 858 |
+
"primary_area": "",
|
| 859 |
+
"author": "Joan Bruna;Christian Szegedy;Ilya Sutskever;Ian Goodfellow;Wojciech Zaremba;Rob Fergus;Dumitru Erhan",
|
| 860 | |
| 861 |
+
"aff": "",
|
| 862 |
+
"aff_domain": "",
|
| 863 |
+
"position": "",
|
| 864 |
+
"rating": "",
|
| 865 |
+
"rating_avg": 0,
|
| 866 |
+
"project": "",
|
| 867 |
+
"github": ""
|
| 868 |
+
},
|
| 869 |
+
{
|
| 870 |
+
"id": "kziQtP-nGqzDb",
|
| 871 |
+
"title": "Learning Human Pose Estimation Features with Convolutional Networks",
|
| 872 |
+
"track": "main",
|
| 873 |
+
"status": "Poster",
|
| 874 |
+
"keywords": "",
|
| 875 |
+
"primary_area": "",
|
| 876 |
+
"author": "Ajrun Jain;Jonathan Tompson;Mykhaylo Andriluka;Graham Taylor;Christoph Bregler",
|
| 877 |
+
"authorids": "[email protected];[email protected];[email protected];[email protected];[email protected]",
|
| 878 |
+
"aff": "",
|
| 879 |
+
"aff_domain": "",
|
| 880 |
+
"position": "",
|
| 881 |
+
"rating": "",
|
| 882 |
+
"rating_avg": 0,
|
| 883 |
+
"project": "",
|
| 884 |
+
"github": ""
|
| 885 |
+
},
|
| 886 |
+
{
|
| 887 |
+
"id": "l-BU-GGdtAlmX",
|
| 888 |
+
"title": "Generative NeuroEvolution for Deep Learning",
|
| 889 |
+
"track": "main",
|
| 890 |
+
"status": "Poster",
|
| 891 |
+
"keywords": "",
|
| 892 |
+
"primary_area": "",
|
| 893 |
+
"author": "Phillip Verbancsics;Josh Harguess",
|
| 894 |
+
"authorids": "[email protected];[email protected]",
|
| 895 |
+
"aff": "",
|
| 896 |
+
"aff_domain": "",
|
| 897 |
+
"position": "",
|
| 898 |
+
"rating": "",
|
| 899 |
+
"rating_avg": 0,
|
| 900 |
+
"project": "",
|
| 901 |
+
"github": ""
|
| 902 |
+
},
|
| 903 |
+
{
|
| 904 |
+
"id": "mQPhQwYHsGQ31",
|
| 905 |
+
"title": "Learned versus Hand-Designed Feature Representations for 3d Agglomeration",
|
| 906 |
+
"track": "main",
|
| 907 |
+
"status": "Poster",
|
| 908 |
+
"keywords": "",
|
| 909 |
+
"primary_area": "",
|
| 910 |
+
"author": "John A. Bogovic;Gary B. Huang;Viren Jain",
|
| 911 |
+
"authorids": "[email protected];[email protected];[email protected]",
|
| 912 |
+
"aff": "",
|
| 913 |
+
"aff_domain": "",
|
| 914 |
+
"position": "",
|
| 915 |
+
"rating": "",
|
| 916 |
+
"rating_avg": 0,
|
| 917 |
+
"project": "",
|
| 918 |
+
"github": ""
|
| 919 |
+
},
|
| 920 |
+
{
|
| 921 |
+
"id": "mugzy2nI-Ayi1",
|
| 922 |
+
"title": "Learning Non-Linear Feature Maps, With An Application To Representation Learning",
|
| 923 |
+
"track": "main",
|
| 924 |
+
"status": "Poster",
|
| 925 |
+
"keywords": "",
|
| 926 |
+
"primary_area": "",
|
| 927 |
+
"author": "Dimitrios Athanasakis;John Shawe-Taylor;Delmiro Fernandez-Reyes",
|
| 928 |
+
"authorids": "[email protected];[email protected];[email protected]",
|
| 929 |
+
"aff": "",
|
| 930 |
+
"aff_domain": "",
|
| 931 |
+
"position": "",
|
| 932 |
+
"rating": "",
|
| 933 |
+
"rating_avg": 0,
|
| 934 |
+
"project": "",
|
| 935 |
+
"github": ""
|
| 936 |
+
},
|
| 937 |
+
{
|
| 938 |
+
"id": "nF5CFb0ZQBFDr",
|
| 939 |
+
"title": "Sequentially Generated Instance-Dependent Image Representations for Classification",
|
| 940 |
+
"track": "main",
|
| 941 |
+
"status": "Poster",
|
| 942 |
+
"keywords": "",
|
| 943 |
+
"primary_area": "",
|
| 944 |
+
"author": "Matthieu Cord;patrick gallinari;Nicolas Thome;Ludovic Denoyer;Gabriel Dulac-Arnold",
|
| 945 |
+
"authorids": "[email protected];[email protected];[email protected];[email protected];[email protected]",
|
| 946 |
+
"aff": "",
|
| 947 |
+
"aff_domain": "",
|
| 948 |
+
"position": "",
|
| 949 |
+
"rating": "",
|
| 950 |
+
"rating_avg": 0,
|
| 951 |
+
"project": "",
|
| 952 |
+
"github": ""
|
| 953 |
+
},
|
| 954 |
+
{
|
| 955 |
+
"id": "nny0nGJmvYs2b",
|
| 956 |
+
"title": "Zero-Shot Learning and Clustering for Semantic Utterance Classification",
|
| 957 |
+
"track": "main",
|
| 958 |
+
"status": "Poster",
|
| 959 |
+
"keywords": "",
|
| 960 |
+
"primary_area": "",
|
| 961 |
+
"author": "Yann N. Dauphin;Gokhan Tur;Dilek Hakkani-Tur;Larry Heck",
|
| 962 |
+
"authorids": "[email protected];[email protected];[email protected];[email protected]",
|
| 963 |
+
"aff": "",
|
| 964 |
+
"aff_domain": "",
|
| 965 |
+
"position": "",
|
| 966 |
+
"rating": "",
|
| 967 |
+
"rating_avg": 0,
|
| 968 |
+
"project": "",
|
| 969 |
+
"github": ""
|
| 970 |
+
},
|
| 971 |
+
{
|
| 972 |
+
"id": "oXSw7laxwUpln",
|
| 973 |
+
"title": "An Empirical Investigation of Catastrophic Forgeting in Gradient-Based Neural Networks",
|
| 974 |
+
"track": "main",
|
| 975 |
+
"status": "Poster",
|
| 976 |
+
"keywords": "",
|
| 977 |
+
"primary_area": "",
|
| 978 |
+
"author": "Yoshua Bengio;Mehdi Mirza;Ian Goodfellow;Aaron Courville;Xia Da",
|
| 979 |
+
"authorids": "[email protected];[email protected];[email protected];[email protected];[email protected]",
|
| 980 |
+
"aff": "",
|
| 981 |
+
"aff_domain": "",
|
| 982 |
+
"position": "",
|
| 983 |
+
"rating": "",
|
| 984 |
+
"rating_avg": 0,
|
| 985 |
+
"project": "",
|
| 986 |
+
"github": ""
|
| 987 |
+
},
|
| 988 |
+
{
|
| 989 |
+
"id": "pAi8PkmKuJPvU",
|
| 990 |
+
"title": "Nonparametric Weight Initialization of Neural Networks via Integral Representation",
|
| 991 |
+
"track": "main",
|
| 992 |
+
"status": "Poster",
|
| 993 |
+
"keywords": "",
|
| 994 |
+
"primary_area": "",
|
| 995 |
+
"author": "Sho Sonoda;Noboru Murata",
|
| 996 |
+
"authorids": "[email protected];[email protected]",
|
| 997 |
+
"aff": "",
|
| 998 |
+
"aff_domain": "",
|
| 999 |
+
"position": "",
|
| 1000 |
+
"rating": "",
|
| 1001 |
+
"rating_avg": 0,
|
| 1002 |
+
"project": "",
|
| 1003 |
+
"github": ""
|
| 1004 |
+
},
|
| 1005 |
+
{
|
| 1006 |
+
"id": "plS31K743MGWn",
|
| 1007 |
+
"title": "A Primal-Dual Method for Training Recurrent Neural Networks Constrained by the Echo-State Property",
|
| 1008 |
+
"track": "main",
|
| 1009 |
+
"status": "Poster",
|
| 1010 |
+
"keywords": "",
|
| 1011 |
+
"primary_area": "",
|
| 1012 |
+
"author": "Jianshu Chen;Li Deng",
|
| 1013 |
+
"authorids": "[email protected];[email protected]",
|
| 1014 |
+
"aff": "",
|
| 1015 |
+
"aff_domain": "",
|
| 1016 |
+
"position": "",
|
| 1017 |
+
"rating": "",
|
| 1018 |
+
"rating_avg": 0,
|
| 1019 |
+
"project": "",
|
| 1020 |
+
"github": ""
|
| 1021 |
+
},
|
| 1022 |
+
{
|
| 1023 |
+
"id": "qqUMpzcNswxen",
|
| 1024 |
+
"title": "Deep Convolutional Ranking for Multilabel Image Annotation",
|
| 1025 |
+
"track": "main",
|
| 1026 |
+
"status": "Poster",
|
| 1027 |
+
"keywords": "",
|
| 1028 |
+
"primary_area": "",
|
| 1029 |
+
"author": "Sergey Ioffe;Alexander Toshev;Yangqing Jia;Thomas Leung;Yunchao Gong",
|
| 1030 |
+
"authorids": "[email protected];[email protected];[email protected];[email protected];[email protected]",
|
| 1031 |
+
"aff": "",
|
| 1032 |
+
"aff_domain": "",
|
| 1033 |
+
"position": "",
|
| 1034 |
+
"rating": "",
|
| 1035 |
+
"rating_avg": 0,
|
| 1036 |
+
"project": "",
|
| 1037 |
+
"github": ""
|
| 1038 |
+
},
|
| 1039 |
+
{
|
| 1040 |
+
"id": "srkxraD5zAMCX",
|
| 1041 |
+
"title": "Correlation-based construction of neighborhood and edge features",
|
| 1042 |
+
"track": "main",
|
| 1043 |
+
"status": "Poster",
|
| 1044 |
+
"keywords": "",
|
| 1045 |
+
"primary_area": "",
|
| 1046 |
+
"author": "Bal\u00e1zs K\u00e9gl",
|
| 1047 |
+
"authorids": "[email protected]",
|
| 1048 |
+
"aff": "",
|
| 1049 |
+
"aff_domain": "",
|
| 1050 |
+
"position": "",
|
| 1051 |
+
"rating": "",
|
| 1052 |
+
"rating_avg": 0,
|
| 1053 |
+
"project": "",
|
| 1054 |
+
"github": ""
|
| 1055 |
+
},
|
| 1056 |
+
{
|
| 1057 |
+
"id": "tPCrkaLa9Y5ld",
|
| 1058 |
+
"title": "One-Shot Adaptation of Supervised Deep Convolutional Models",
|
| 1059 |
+
"track": "main",
|
| 1060 |
+
"status": "Poster",
|
| 1061 |
+
"keywords": "",
|
| 1062 |
+
"primary_area": "",
|
| 1063 |
+
"author": "Trevor Darrell;Eric Tzeng;Yangqing Jia;Judy Hoffman;Kate Saenko;Jeff Donahue",
|
| 1064 | |
| 1065 |
+
"aff": "",
|
| 1066 |
+
"aff_domain": "",
|
| 1067 |
+
"position": "",
|
| 1068 |
+
"rating": "",
|
| 1069 |
+
"rating_avg": 0,
|
| 1070 |
+
"project": "",
|
| 1071 |
+
"github": ""
|
| 1072 |
+
},
|
| 1073 |
+
{
|
| 1074 |
+
"id": "u-IAYCzRsK-vN",
|
| 1075 |
+
"title": "Sparse similarity-preserving hashing",
|
| 1076 |
+
"track": "main",
|
| 1077 |
+
"status": "Poster",
|
| 1078 |
+
"keywords": "",
|
| 1079 |
+
"primary_area": "",
|
| 1080 |
+
"author": "Alex M. Bronstein;Guillermo Sapiro;Pablo Sprechmann;Jonathan Masci;Michael M. Bronstein",
|
| 1081 |
+
"authorids": "[email protected];[email protected];[email protected];[email protected];[email protected]",
|
| 1082 |
+
"aff": "",
|
| 1083 |
+
"aff_domain": "",
|
| 1084 |
+
"position": "",
|
| 1085 |
+
"rating": "",
|
| 1086 |
+
"rating_avg": 0,
|
| 1087 |
+
"project": "",
|
| 1088 |
+
"github": ""
|
| 1089 |
+
},
|
| 1090 |
+
{
|
| 1091 |
+
"id": "uuFh8Ny0WPw0B",
|
| 1092 |
+
"title": "Some Improvements on Deep Convolutional Neural Network Based Image Classification",
|
| 1093 |
+
"track": "main",
|
| 1094 |
+
"status": "Poster",
|
| 1095 |
+
"keywords": "",
|
| 1096 |
+
"primary_area": "",
|
| 1097 |
+
"author": "Andrew Howard",
|
| 1098 |
+
"authorids": "[email protected]",
|
| 1099 |
+
"aff": "",
|
| 1100 |
+
"aff_domain": "",
|
| 1101 |
+
"position": "",
|
| 1102 |
+
"rating": "",
|
| 1103 |
+
"rating_avg": 0,
|
| 1104 |
+
"project": "",
|
| 1105 |
+
"github": ""
|
| 1106 |
+
},
|
| 1107 |
+
{
|
| 1108 |
+
"id": "vz8AumxkAfz5U",
|
| 1109 |
+
"title": "Revisiting Natural Gradient for Deep Networks",
|
| 1110 |
+
"track": "main",
|
| 1111 |
+
"status": "Poster",
|
| 1112 |
+
"keywords": "",
|
| 1113 |
+
"primary_area": "",
|
| 1114 |
+
"author": "Razvan Pascanu;Yoshua Bengio",
|
| 1115 |
+
"authorids": "[email protected];[email protected]",
|
| 1116 |
+
"aff": "",
|
| 1117 |
+
"aff_domain": "",
|
| 1118 |
+
"position": "",
|
| 1119 |
+
"rating": "",
|
| 1120 |
+
"rating_avg": 0,
|
| 1121 |
+
"project": "",
|
| 1122 |
+
"github": ""
|
| 1123 |
+
},
|
| 1124 |
+
{
|
| 1125 |
+
"id": "wxobw18IYOxu4",
|
| 1126 |
+
"title": "Group-sparse Embeddings in Collective Matrix Factorization",
|
| 1127 |
+
"track": "main",
|
| 1128 |
+
"status": "Poster",
|
| 1129 |
+
"keywords": "",
|
| 1130 |
+
"primary_area": "",
|
| 1131 |
+
"author": "Arto Klami;Guillaume Bouchard;Abhishek Tripathi",
|
| 1132 |
+
"authorids": "[email protected];[email protected];[email protected]",
|
| 1133 |
+
"aff": "",
|
| 1134 |
+
"aff_domain": "",
|
| 1135 |
+
"position": "",
|
| 1136 |
+
"rating": "",
|
| 1137 |
+
"rating_avg": 0,
|
| 1138 |
+
"project": "",
|
| 1139 |
+
"github": ""
|
| 1140 |
+
},
|
| 1141 |
+
{
|
| 1142 |
+
"id": "ylE6yojDR5yqX",
|
| 1143 |
+
"title": "Network In Network",
|
| 1144 |
+
"track": "main",
|
| 1145 |
+
"status": "Poster",
|
| 1146 |
+
"keywords": "",
|
| 1147 |
+
"primary_area": "",
|
| 1148 |
+
"author": "Min Lin;Qiang Chen;Shuicheng Yan",
|
| 1149 |
+
"authorids": "[email protected];[email protected];[email protected]",
|
| 1150 |
+
"aff": "",
|
| 1151 |
+
"aff_domain": "",
|
| 1152 |
+
"position": "",
|
| 1153 |
+
"rating": "",
|
| 1154 |
+
"rating_avg": 0,
|
| 1155 |
+
"project": "",
|
| 1156 |
+
"github": ""
|
| 1157 |
+
},
|
| 1158 |
+
{
|
| 1159 |
+
"id": "z6PozRtCowzLe",
|
| 1160 |
+
"title": "Modeling correlations in spontaneous activity of visual cortex with centered Gaussian-binary deep Boltzmann machines",
|
| 1161 |
+
"track": "main",
|
| 1162 |
+
"status": "Poster",
|
| 1163 |
+
"keywords": "",
|
| 1164 |
+
"primary_area": "",
|
| 1165 |
+
"author": "nan wang;Laurenz Wiskott;Dirk Jancke",
|
| 1166 |
+
"authorids": "[email protected];[email protected];[email protected]",
|
| 1167 |
+
"aff": "",
|
| 1168 |
+
"aff_domain": "",
|
| 1169 |
+
"position": "",
|
| 1170 |
+
"rating": "",
|
| 1171 |
+
"rating_avg": 0,
|
| 1172 |
+
"project": "",
|
| 1173 |
+
"github": ""
|
| 1174 |
+
}
|
| 1175 |
+
]
|
iclr/iclr2017.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
iclr/iclr2018.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|