This page is outdated. For more recent MLDG, please go to http://wiki.cs.cornell.edu/index.php?title=Machine_Learning_Discussion_Group
- Machine Learning Reading Group
- Admins: Nikos, Ainur, Ruben
What is the MLDG?
It is an informal group for discussing the latest work in the field of Machine Learning. We usually discuss a paper from a recent conference(NIPS,ICML..) each meeting.
When and where do we meet?
This Fall Spring we will meet every Wednesday@4:30pm in 5126 Upson.
Who attends the MLDG?
The group is mainly attended by graduate students. The senior organizers are Nikos, Ainur and Ruben Sipos. Suggestions for topics or papers to discuss are always welcome.
Mailing List
Sign up to receive updates at our mailing list here.
Latest News
- Anshumali, Hema and Abhishek all had papers accepted at NIPS.
Friday@4:00pm in 344 Gates Hall (Breakout room).
Papers Read
- Fall 2013
Date | Presenter | Topic(s) | Resources/Papers | Other activities/ comments |
|---|---|---|---|---|
9/6/2013 | Ruben | General ML |
| |
9/20/2013 | Karthik | Active Learning, Crowdsourcing | Tutorial style discussion. | Paul Bennett (AI Seminar) |
9/27/2013 | Ashwin | Method of moments | A bit of background from |
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10/4/2013 | Adith | Distributed Representations | Freeform discussion. |
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10/18/2013 | Hema | Vision | - |
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10/25/2013 | Chenhao | Practice Talk | - |
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11/1/2013 | Ashesh | Human-In-Loop Learning | Fine-Grained Crowd sourcing for Fine-Grained Recognition |
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11/15/2013 | Stefano |
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11/22/2013 | Yin |
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- Summer 2013
Date | Topic | Paper | Discussion Leader |
|---|---|---|---|
7/18 | Inverse Reinforcement Learning | Tutorial | Ashesh |
7/11 | Bayesian Nonparametrics | Dirichlet processes, its variants and applications | Yun |
6/27 | Deep Learning | Deep Learning (Examples, Thoughts and Ideas) | Moontae |
6/13 | Bioinformatics | Tutorial on Machine Learning problems in Bioinformatics and Genetics | Brad |
6/6 | Structured Learning | Ruben | |
5/23 | Deep Learning | Tutorial on Deep Learning | Ian |
- Spring 2013
Date | Topic | Paper | Discussion Leader |
|---|---|---|---|
4/26 | Locality-Sensitive Hashing | Anshu | |
4/12 | Metric Learning | Ozan | |
4/5 | Metric Learning | Karthik | |
3/15 | Submodularity | Karthik | |
3/08 | Large-Scale Learning | Anshumali | |
3/01 | Large-Scale Learning | Scaling Up Coordinate Descent Algorithms for Large L_1 Regularization Problems | Ashesh |
2/22 | Causal Learning | Chenhao | |
2/15 | Submodularity | Ruben | |
2/8 | Large-Scale Learning | Moontae |
- Fall 2012
Date | Topic | Paper | Discussion Leader |
|---|---|---|---|
11/16 | Submodularity | Learning Mixtures of Submodular Shells with Application to Document Summarization | Ruben & Karthik |
11/9 | Generative Models | Exploiting compositionality to explore a large space of model structures | Jason |
10/19 | Generative Models | Revisiting k-means: New Algorithms via Bayesian Nonparametrics | Karthik |
10/12 | Generative Models | Ruben | |
9/28 | Generative Models | Adith | |
9/14 | Time Series Analysis | Searching and Mining Trillions of Time Series Subsequences under Dynamic Time Warping | Ashesh |
9/7 | Statistical Estimators | Karthik |
- Spring 2012
Date | Topic | Paper | Discussion Leader |
|---|---|---|---|
4/6 | Machine Learning and Game Theory | Karthik |
...
- Fall 2011
Date | Topic | Paper | Discussion Leader | |
|---|---|---|---|---|
11/2 | Deep Learning | Parsing Natural Scenes and Natural Language with Recursive Neural Networks | Abhishek & Ainur |
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10/19 | Graphical Models | Spectral Algorithm for Latent Tree Graphical Models | Karthik | |
10/5 |
| Trading Representability for Scalability: Adaptive Multi-Hyperplane Machine for Nonlinear Classification | Nikos | |
9/28 | Submodularity | Submodularity tutorial | Ashwin | |
9/21 | Graphical Models | Nikos | ||
9/14 | Submodularity | Karthik | ||
9/7 | Deep-Learning, Graphical Models | TBD Karthik |
- Spring 2011
Date | Topic | Paper | Discussion Leader |
|---|---|---|---|
4/29, 5/6, 5/13 | Variational Methods | Nikos | |
4/22 | Deep Learning | Ainur | |
4/15 | Deep Learning | Akram | |
4/8 | Deep Learning | Akram | |
4/1 | Semi-Supervised Learning | Nikos | |
3/11 | Game Theory and Learning | Ruben | |
3/4 | Game Theory and Learning | Karthik | |
2/25 | Multi-Task Learning | Tree-Guided Group Lasso for Multi-Task Regression with Structured Sparsity | Bishan |
...
Date | Topic | Paper | Discussion Leader |
|---|---|---|---|
11/12 | Vision | Jason | |
11/5 | Metric Learning | Karthik | |
10/29 | Clustering | Ruben |
Who attends the MLDG?
The group is mainly attended by graduate students. The senior organizers are Ruben and Karthik. Suggestions for topics or papers to discuss are always welcome.
Mailing List
Sign up to receive updates at our mailing list here.