Machine Learning Reading Group
Summer 2010
Welcome to the Machine Learning Reading Group at Brown University. We meet in CIT 345 on most Thursdays at 12:00pm 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 Jason Pacheco. If you have an ongoing or just-completed project involving machine learning, please offer to lead a session!
Schedule
Date | Topic | Discussion leaders |
---|---|---|
May 27 | Organizational Meeting | |
Jun 10 | Graphical Models for Visual Object Recognition and Tracking Section 2.3.2, Belief Propagation (pp 69-79) E. Sudderth, Ph.D. Thesis |
Jason Pacheco |
Jun 24 | Sections 1-4, Pages 1-19: Introduction to Statistical Learning Theory O. Bousquet, S. Boucheron, G. Lugosi |
Jeff Miller |
Jul 08 | Tutorial: Techniques for Debugging MCMC Samplers Some Useful References: 1) Chapter 11.2, 11.3 Pattern Recognition and Machine Learning C. Bishop 2) Chapter 2.4: Monte Carlo Methods Graphical Models for Visual Object Recognition and Tracking E. Sudderth, Ph.D. Thesis 3)An Introduction to MCMC for Machine learning C. Andrieu 4)Introduction to Monte Carlo Methods D.J.C. Mackay |
Micha Elsner |
Aug 3 | Invited Talk: Towards Decision-Theoretic Teaching: Sequential Planning Under Uncertainty in Domains Inspired By Tutoring |
Emma Brunskill |
Aug 12 | The Infinite Factorial Hidden Markov Model J. V. Gael, Y. W. Teh, Z. Ghahramani |
Deepak Santhanam |