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.
This Spring we will meet every Friday@4:00pm in 344 Gates Hall (Breakout room).
Date | Presenter | Topic(s) | Resources/Papers | Other activities/ comments |
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9/6/2013 | Ruben | General ML |
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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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Date | Topic | Paper | Discussion Leader |
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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 |
Date | Topic | Paper | Discussion Leader |
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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 |
Date | Topic | Paper | Discussion Leader |
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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 |
Date | Topic | Paper | Discussion Leader |
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4/6 | Machine Learning and Game Theory | Karthik |
Date | Topic | Paper | Discussion Leader | |
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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 | Karthik |
Date | Topic | Paper | Discussion Leader |
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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 |
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11/12 | Vision | Jason | |
11/5 | Metric Learning | Karthik | |
10/29 | Clustering | Ruben |
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.
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