[Artificial Intelligence and Statistics Logo] Artificial Intelligence and Statistics 2009


AISTATS*09 Schedule

Wednesday, April 15
4.00 - 6.00: Registration (Salons D-G Foyer)
6.00 - 7.30: Opening Reception (Salons D-G Foyer)
Thursday, April 16
8.15 - 9.00: Conference Breakfast
9.00 - 10.20: Snowbird (four 20 minute talks)
10.20 - 10.45: Coffee Break
10.45 - 12.00: Probability Models (Chair N. Lawrence)
  Probabilistic Models for Incomplete Multi-dimensional Arrays; W. Chu, Z. Ghahramani
  Relational Topic Models for Document Network; J. Chang, D. Blei
  Exploiting Probabilistic Independence for Permutations; J. Huang, C. Guestrin, X. Jiang, L. Guibas
12.00 - 4.00: Break
4.00 - 5.15: Planning and Control (Chair C. Guestrin)
  Inverse Optimal Heuristic Control for Imitation Learning; N. Ratliff, B. Ziebart, K. Peterson, J. Bagnell, M. Hebert, S. Srinivasa
  Data Biased Robust Counter Strategies; M. Johanson, M. Bowling
  Learning Exercise Policies for American Options; Y. Li, C. Szepesvari, D. Schuurmans
5.15 - 8.00: Poster Session I
8.00 - 9.30: Conference Banquet (Mark Hanson, speaker)
Friday, April 17
8.15 - 9.00: Conference Breakfast
9.00 - 10.15: Inference and Structure Learning (Chair M. Girolami)
  Tractable Bayesian Inference of Time-Series Dependence Structure; M. Siracusa, J. Fisher III
  Learning Thin Junction Trees via Graph Cuts; S. Dafna, C. Guestrin
  Exact and Approximate Sampling by Systematic Stochastic Search; V. Mansinghka, D. Roy, E. Jonas, J.
10.15 - 10.45: Coffee Break
10.45 - 11.55: Invited Speaker: Bill Cleveland
11.55 - 12.20: Latent Force (Chair D. Blei)
  Latent Force Models; M. Alvarez, D. Luengo, N. Lawrence
12.30 - 3.30: Break
3.30 - 4.20: Learning Theory (Chair C. Crammer)
  Chromatic PAC-Bayes Bounds for Non-IID Data; L. Ralaivola, M. Szafranski, G. Stempfel
  Estimation Consistency of the Group Lasso and its Applications; H. Liu, J. Zhang
4.20 - 4.45: Coffee Break
4.45 - 6.00: Clustering and Co-Training (Chair M. Meila)
  Clusterability: A Theoretical Study; M. Ackerman, S. Ben-David
  Tighter and Convex Maximum Margin Clustering; Y. Li, T. Ivor W, J. Kwok, Z. Zhou
  Active Sensing in Bayesian Co-Training; S. Yu, B. Krishnapuram, R. Rosales, R. Rao
6.00 - 7.30: Dinner Break
7.30 -10.30: Poster Session II
Saturday, April 18
8.15 - 9.00: Conference Breakfast
9.00 - 10.15: Non Parametric Bayes (Chair R. Silva)
  Variational Inference for the Indian Buffet Process; F. Doshi, K. Miller, J. Van Gael, Y. Teh
  The Block Diagonal Infinite Hidden Markov Model; T. Stepleton, Z. Ghahramani, G. Gordon, T. Lee
  A Hierarchical Nonparametric Bayesian Approach to Statistical Language Model Domain Adaptation; F. Wood, Y. Teh (Best Paper Award)
10.15 - 10.45: Coffee Break
10.45 - 11.55: Invited Speaker: Carlos Carvalho
11.55 - 12.20: Optimization (Chair J. Zhu)
  Optimizing Costly Functions with Simple Constraints: A Limited-Memory Projected Quasi-Newton Algorithm; M. Schmidt, E. van den Berg, M. Friedlander, K. Murphy (Best Paper Award)
12.30 - 2.00: Break
2:00 - 2.50: Network Inference (Chair A. Ihler)
  A kernel method for unsupervised structured network inference; C. Lippert, O. Stegle, Z. Ghahramani, K. Borgwardt
  Network Completion and Survey Sampling; S. Hanneke, E. Xing
3.00 - 6.00: Poster Session III
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