Artificial Intelligence and Statistics 2015

AISTATS 2015 Schedule

Notice

Schedules in this page are tentative, subjec to change without prior notice.
Registration desk will be open 10:30 - 13:30, 15:00 - 17:00 on May 9, 10:00 - 12:00, 16:00 - 18:00 on May 10, and 10:00 - 12:00 on May 11. In case of emergency, please contact Karen Smith (aistats2015.ksmith at gmail.com).

May 9 (Saturday)

Time	Schedule
10:30 - 13:30	Registration desk open ICLR Poster Session (included in AISTATS registration)
15:00 - 17:00	Registration desk open
17:00 - 18:00	Keynote: Pierre Baldi International Ballroom
18:00 - 20:00	Welcome Reception (joint with ICLR) Fresco's

May 10 (Sunday)

Time	Schedule
7:30 - 8:30	Breakfast South Poolside
8:30 - 9:30	Paper Award Announcement Keynote: Kai Yu International Ballroom
9:30 - 10:00	Coffee break
10:00 - 12:00	Oral Session 1 International Ballroom Computational Complexity of Linear Large Margin Classification With Ramp Loss A la Carte -- Learning Fast Kernels A Scalable Algorithm for Structured Kernel Feature Selection Learning where to Sample in Structured Prediction
12:00 - 14:00	Lunch on your own
14:00 - 16:00	Oral Session 2 International Ballroom Tradeoffs for Space, Time, Data and Risk in Unsupervised Learning Constant Step Size Least-Mean-Squares: Bias-Variance Trade-offs and Optimal Sampling Distributions Sparsistency of l_1-Regularized M-Estimators Two-stage sampled learning theory on distributions
16:00 - 16:30	Coffee break
16:30 - 18:30	Oral Session 3 International Ballroom Generalized Linear Models for Aggregated Data Efficient Estimation of Mutual Information for Strongly Dependent Variables Understanding and Evaluating Sparse Linear Discriminant Analysis Back to the Past: Source Identification in Diffusion Networks
18:30 - 19:30	Dinner on your own
19:30 - 22:00	Poster Session 1 Pavilion

May 11 (Monday)

Time	Schedule
7:30 - 8:30	Breakfast South Poolside
8:30 - 9:30	Keynote: Mark Hansen International Ballroom
9:30 - 10:00	Coffee break
10:00 - 12:00	Oral Session 4 International Ballroom Sparse Submodular Probabilistic PCA Unifying Local Consistency and MAX SAT Relaxations for Scalable Inference with Rounding Guarantees Low-Rank Spectral Learning with Weighted Loss Functions A Spectral Algorithm for Inference in Hidden semi-Markov Models
12:00 - 14:00	Lunch on your own
14:00 - 16:00	Oral Session 5 International Ballroom Stochastic Spectral Descent for Restricted Boltzmann Machines Sparse Dueling Bandits Online Ranking with Top-1 Feedback Fast Function to Function Regression
16:00 - 16:30	Coffee break
16:30 - 18:30	Oral Session 6 International Ballroom The Security of Latent Dirichlet Allocation Modeling Skill Acquisition Over Time with Sequence and Topic Modeling Dirichlet Process Mixture Model for Spherical Data Tensor Factorization via Matrix Factorization
18:30 - 19:30	Dinner on your own
19:30 - 22:00	Poster Session 2 Pavilion

May 12 (Tuesday)

Time	Schedule
7:30 - 8:30	Breakfast South Poolside
8:30 - 9:30	Keynote: Deepak Agarwal International Ballroom
9:30 - 10:00	Coffee break
10:00 - 11:30	Oral Session 7 International Ballroom Exact Bayesian Learning of Ancestor Relations in Bayesian Networks Parameter Estimation of Generalized Linear Models without Assuming their Link Function Stochastic Block Transition Models for Dynamic Networks
11:30 - 13:00	Farewell Lunch South Poolside

This site last compiled Mon, 09 Jan 2023 17:13:01 +0000

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