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Opening Remarks
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In Search of New Algorithms Part I: Neural Networks
Adam Klivans (University of Texas at Austin)
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Break
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In Search of New Algorithms Part II: Graphical Models
Adam Klivans (University of Texas at Austin)
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Lunch
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The Fine Line between Hard and Easy Inference Problems: The View from CSPs
Boaz Barak (Harvard)
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Break
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The Fine Line between Hard and Easy Inference Problems: The View from CSPs (continued)
Boaz Barak (Harvard)
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Reception
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Lower Bounds on Statistical Estimation Rates Under Various Constraints
Po-Ling Loh (University of Cambridge)
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Break
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Lower Bounds on Statistical Estimation Rates Under Various Constraints (continued)
Po-Ling Loh (University of Cambridge)
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Lunch
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On Algorithms and Barriers of Intractability in High-Dimensional Statistical Inference
Prasad Raghavendra (UC Berkeley)
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Break
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On Algorithms and Barriers of Intractability in High-Dimensional Statistical Inference (continued)
Prasad Raghavendra (UC Berkeley)
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Lower Bounds on Statistical Estimation Rates Under Various Constraints
Po-Ling Loh (University of Cambridge)
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Break
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Lower Bounds on Statistical Estimation Rates Under Various Constraints (continued)
Po-Ling Loh (University of Cambridge)
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Lunch
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On Algorithms and Barriers of Intractability in High-Dimensional Statistical Inference
Prasad Raghavendra (UC Berkeley)
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Break
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On Algorithms and Barriers of Intractability in High-Dimensional Statistical Inference (continued)
Prasad Raghavendra (UC Berkeley)
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Average-Case Complexity Theory
Luca Trevisan (Bocconi University)
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Break
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Average-Case Complexity Theory (continued)
Luca Trevisan (Bocconi University)
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Lunch
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Approximate Message Passing Algorithms
Cynthia Rush (Columbia University)
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Break
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Approximate Message Passing Algorithms (continued)
Cynthia Rush (Columbia University)
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Average-Case Complexity Theory
Luca Trevisan (Bocconi University)
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Break
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Average-Case Complexity Theory (continued)
Luca Trevisan (Bocconi University)
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Lunch
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Optimal Iterative Algorithms for Problems With Random Data
Andrea Montanari (Stanford)
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Break
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Optimal Iterative Algorithms for Problems With Random Data
Andrea Montanari (Stanford)