jingyangcarl commited on
Commit
79dc07f
·
verified ·
1 Parent(s): d8a5384

Upload folder using huggingface_hub

Browse files
This view is limited to 50 files because it contains too many changes.   See raw diff
.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
- license: mit
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
+ ![Showcase](tools/img/image.png)
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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