Welcome to the Machine Learning Reading Group at Brown University. We meet in CIT Room 345 on Fridays at 1pm and are open to all students and faculty.
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.
Our topics this semester are log-linear models, belief propagation, gaussian processes, and Variational Bayes. We will also be hosting some invited talks, speakers permitting. If you have an ongoing or just-completed project involving machine learning, please offer to lead a session!
| Date | Topic | Discussion leaders |
|---|---|---|
| January 30th | Organizational Meeting Bring papers and topics |
Everyone |
| February 6th | Intro to MaxEnt Principle and Log-linear models Main reading: Sutton and McCallum 2006 (only pages 1-24) Supplemental: Lafferty, McCallum, and Pereira, ICML 2001 Excellent slides: Klein and Manning 2003 |
Matt Lease and David McClosky |
| February 13th | Log-linear models and CRFs Same readings as previous week |
Matt Lease and David McClosky |
| February 20th | Log-linear models: Estimation Main reading: Berger 1997 Supplemental: Globerson, Koo, Carreras, and Collins, ICML 2007 Slides: Klein and Manning 2003 are still relevant. |
Will Headden |
| February 29th | Belief Propagation Reading: Yedidia, Freeman, and Weiss 2002 (sections 1.2 and 2) Aggeliki's slides: (PPT) (PDF) |
Aggeliki Tsoli |
| March 7th | Belief Propagation Same paper as previous week (read later sections) |
Jesse Butterfield |
| March 14th | No meeting this week due to job talk | Job talks |
| March 21st | Nuts and Boltzmann Tutorials: Scholarpedia and Sam Roweis's notes Application and extension: Hinton, Osindero, and Teh (2006) |
Everyone |
| March 21st | Principal Geodesic Analysis Optional readings: Wu, Smith, and Hancock (2006) (sections 1-3) Fletcher, Lu, Pizer, and Joshi (2004) (sections II.B-C, III, and IV) |
David Hirshberg and Jason Pacheco |
| April 4th | No meeting this week due to job talks | Job talks |
| April 11th | Two-view Feature Generation Model for Semi-supervised Learning Ando and Zhang (ICML 2007) |
Everyone |
| April 18th | Learning Multiscale Representations of Natural Scenes Using Dirichlet Processes Jyri Kivinen, Erik Sudderth, and Michael Jordan (ICCV 2007) |
Everyone |
| April 25th | Introduction to Variational Bayes Tutorial by Tommi Jaakkola (sections 4, 5, and 8) |
Will Headden |
| May 2nd | Variational Bayes Beal and Ghahramani (2004) (sections 2, 3.1, 3.4, 3.5) |
Everyone |
| May 30th | Variational Bayes...once more Tutorial by Tommi Jaakkola (sections 8 and 7) |
Everyone |
Conferences and journals:
Some ML deadlines:
Links: