Machine Learning Reading Group
Fall 2012
Welcome to the Machine Learning Reading Group at Brown University. We meet in CIT 345 on most Thursdays a 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 Mike Hughes. Please email:
mhughes AT cs.brown.edu
If you have an ongoing or just-completed project involving machine
learning, please offer to lead a session!
Schedule
Date | Topic | Discussion leaders |
---|---|---|
Sept 6 | Bayesian Checking for Topic Models D. Mimno & D. Blei Inspired by This post on Gelman's blog. |
Thomas Wiecki |
Sept 13 | Introduction to ML Software STAN (Gelman et al.) BUGS (Bayesian inference using Gibbs Sampling) |
various artists |
Oct 4 | Learning individual and population level traits from clinical temporal data [PDF] Suchi Saria, D. Koller, and A. Penn |
Mark Homer |
Oct 4 | Effective Split-Merge Inference for Nonparametric Models of Sequential Data [PDF] M. Hughes, E. Fox, and E. Sudderth |
Mike Hughes |
Oct 29 | The discovery of structural form [PDF] Kemp and Tennenbaum |
Jeff Miller |
Nov 11 | Practical Bayesian Optimization of Machine Learning Algorithms arXiv J. Snoek, H. Larochelle, and Ryan Adams |
Mike Hughes |
Nov 11 | Truncation-free Stochastic Variational Inference for Bayesian Nonparametric Models Chong Wang and David Blei |
Mike Hughes |
Nov 23 | Priors for diversity in generative latent variable models James Zhou and Ryan Adams |
Soumya Ghosh |