Structure and Randomness in System Identification and Learning - IPAM

Structure and Randomness in System Identification and Learning

January 15 - 18, 2013

Schedule

All times in this Schedule are Pacific Time (PT)

Tuesday, January 15, 2013

Morning Session

08:00-09:00
Check-In/Light Breakfast (Hosted by IPAM)
09:00-09:50
Pablo Parrilo (Massachusetts Institute of Technology)
Convex Sets, Conic Matrix Factorizations and Conic Rank Lower Bounds
10:00-10:15
Break
10:15-11:05
Tong Zhang (Rutgers University-Camden)
Proximal Stochastic Dual Coordinate Ascent
11:15-11:30
Break
11:30-12:20
Constantine Caramanis (University of Texas at Austin)
Crowd-Sourcing Epidemic Detection

Afternoon Session

12:30-14:30
Lunch (on your own)
14:30-15:20
Munther Dahleh (Massachusetts Institute of Technology)
Rare Probability Estimation
15:30-16:00
Break
16:00-16:50
John Doyle (California Institute of Technology)
What is the probability that Munzer will see something that does not exist? A Bayesian Perspective
17:00-18:30
Reception and Poster Session (Hosted by IPAM)

Wednesday, January 16, 2013

Morning Session

08:00-09:00
Continental Breakfast
09:00-09:50
Lennart Ljung (Linköping University)
Using Multiple Kernel-based Regularization for Linear System Identification
10:00-10:15
Break
10:15-11:05
Mario Sznaier (Northeastern University)
Moments Based Relaxations in Systems Identification and Machine Learning
11:15-11:30
Break
11:30-12:20
Venkat Chandrasekaran (California Institute of Technology)
Computational and Statistical Tradeoffs via Convex Relaxation

Afternoon Session

12:30-14:30
Lunch (on your own)
14:30-15:20
Stephen Wright (University of Wisconsin-Madison)
Convergence of a Randomized Sampling Method for Identifying a Subspace of R^n.
15:30-16:00
Break
16:00-16:50
Lin Xiao (Microsoft Research)
Proximal-Gradient Homotopy Methods for Sparse Optimization

Thursday, January 17, 2013

Morning Session

08:00-09:00
Continental Breakfast
09:00-09:50
Emmanuel Candes (Stanford University)
Towards a Mathematical Theory of Super-Resolution
10:00-10:15
Break
10:15-11:05
Andrea Montanari (Stanford University)
Hypothesis Testing in High-Dimensional Regression under the Gaussian Random Design Model
11:15-11:30
Break
11:30-12:20
Alekh Agarwal (Microsoft Research)
Stochastic Optimization and Sparse Statistical Recovery: An Optimal Algorithm in High Dimensions

Afternoon Session

12:30-14:00
Lunch (on your own)
14:00-14:50
Michael Mahoney (Stanford University)
Structure and Randomness in Large Informatics Graphs
15:00-15:15
Break
15:15-16:05
Nathan Srebro (TTI-Chicago)
Tightness of Convex Relaxations to Sparsity and Rank
16:15-16:30
Break
16:30-17:20
Inderjit Dhillon (University of Texas at Austin)
Sparse Inverse Covariance Matrix Estimation Using Quadratic Approximation

Friday, January 18, 2013

Morning Session

08:00-09:00
Continental Breakfast
09:00-09:50
Joel Tropp (California Institute of Technology)
Sharp Recovery Bounds for Convex Demixing with Applications
10:00-10:15
Break
10:15-11:05
Sahand Negahban (Massachusetts Institute of Technology)
Noisy Matrix Decomposition via Convex Relaxation
11:15-11:30
Break
11:30-12:20
Babak Hassibi (California Institute of Technology)
Phase Recovery for Sparse Signals

Afternoon Session

12:30-14:30
Lunch (on your own)
14:30-15:20
Deanna Needell (University of California, Los Angeles (UCLA))
Synthesis and Analysis Type Methods for Signal Reconstruction from Random Observations
15:30-16:00
Break
16:00-16:50
Maryam Fazel (University of Washington)
Simultaneously Structured Models with Application to Sparse and Low-rank Matrices
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