Welcome to the Machine Learning Reading Group at Brown University. We meet in CIT Room 345 on Fridays at 2pm and are open to all students and faculty. (If you can't make this time, please email the group leader.)
MLRG meetings and other news are announced via posts to the ML-READING-GROUP list. You can subscribe here. The MLRG leader this semester is David McClosky.
If you have an ongoing or recently completed project involving machine learning, please offer to lead a session!
| Date | Topic | Unit |
|---|---|---|
| September 5th | A Probabilistic Approach to Language Change Bouchard-Cote, Liang, Griffiths, and Klein (2008) Supplemental: Bouchard-Cote, Liang, Griffiths, and Klein (2007) Presenters: Micha Elsner and David McClosky |
Warm up |
| September 12th | Bring papers and topics! | Organizational |
| September 19th | Text Classification from Labeled and Unlabeled Documents using EM Nigam, McCallum, Thrun, and Mitchell (ML 1999) |
Semi-supervised learning |
| September 26th | Semi-Supervised Support Vector Machines Bennett and Demiriz (1998)
Maximum Margin Semi-Supervised Learning for Structured Variables |
Semi-supervised learning |
| October 3rd | Semi-supervised Convex Training for Dependency Parsing Wang, Schuurmans, and Lin (ACL 2008) |
Semi-supervised learning |
| October 10th | Semi-Supervised Learning Using Gaussian Fields and Harmonic Functions Zhu, Ghahramani, and Lafferty (2003) |
Semi-supervised learning |
| October 17th | On the Gravity Recommendation System Takacs, PIlaszy, Nemeth, and Tikk (2007) |
Collaborative filtering |
| October 24th | The Phylogenetic Indian Buffet Process: A Non-Exchangeable
Nonparametric Prior for Latent Features Miller, Griffiths, and Jordan (UAI 2008) |
Collaborative filtering |
| October 31st | More Netflix Challege papers Two papers (original link, contains other papers as well) The papers are: Jinlong Wu and Tiejun Li. A Modified Fuzzy C-Means Algorithm For Collaborative Filtering Andreas Toescher, Michael Jahrer and Robert Legenstein. Improved Neighborhood-Based Algorithms for Large-Scale Recommender Systems. |
Collaborative filtering |
| November 7th | Closed-form Supervised Dimensionality Reduction with Generalized Linear Models Irina Rish, Genady Grabarnilk, Guillermo Cecchi, Francisco Pereira, and Geoffrey J. Gordon (ICML 2008) |
Collaborative filtering-ish? |
| November 14th | No meeting. | |
| November 21st | Learning nonparametric policies by imitation Grimes and Rao (IROS 2008) |
Non-parametric Bayes |
| November 28th | No meeting | |
| December 5th | An HDP-HMM for Systems with State Persistence Fox, Sudderth, Jordan, and Willsky (ICML 2008) |
Non-parametric Bayes |
Conferences and journals:
Links: