| Date | Presenter | Paper | Authors |
|---|---|---|---|
| 1/14/2014 | Weng-Keen Wong | The Indian Buffet Process: An Introduction and Review (up to Section 2.4) | T. L. Griffiths and Z. Ghahramani |
| 1/21/2014 | Weng-Keen Wong | The Indian Buffet Process: An Introduction and Review (Section 2.4 to the end) | T. L. Griffiths and Z. Ghahramani |
| 1/28/2014 | Shubhomoy Das | Nonparametric Latent Feature Models for Link Prediction | K. T. Miller, T. L. Griffiths and M. I. Jordan |
| 2/4/2014 | Behrooz Mahasseni | Nonparametric Variational Inference | S. J. Gershman, M. D. Hoffman and D. M. Blei |
| 2/11/2014 | Travis Moore | Stochastic Variational Inference (Part 1) | M. D. Hoffman, D. M. Blei, C. Wang and J. Paisley |
| 2/18/2014 | Travis Moore | Stochastic Variational Inference (Part 2) | M. D. Hoffman, D. M. Blei, C. Wang and J. Paisley |
| 3/4/2014 | Weng-Keen Wong | Expectation Propagation for Approximate Bayesian Inference Video Lecture | Thomas P. Minka |
| 3/4/2014 | Andrew Emmott | Copula Bayesian Networks | Gal Elidan |
| 3/11/2014 | Behrooz Mahasseni | Perturb-and-MAP Random Fields: Using Discrete Optimization to Learn and Sample from Energy Models (Appendix) | G. Papandreou and A. L. Yuille |
| TBD | TBD | Multiple Instance Learning on Structured Data | D. Zhang, Y. Liu, L. Si, J. Zhang and R. D. Lawrence |
| TBD | TBD | A Method of Moments for Mixture Models and Hidden Markov Models | A. Anandkumar, D. Hsu and S. M. Kakade |