[Artificial Intelligence and Statistics Logo] Artificial Intelligence and Statistics 2015

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AISTATS 2015 Schedule

Notice


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
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