Upcoming Workshops & Symposia

Deep Learning Reunion
Aug. 10 – Aug. 14, 2020
Program: Foundations of Deep Learning

Organizers:

Samy Bengio (Google), Aleksander Mądry (Massachusetts Institute of Technology), Elchanan Mossel (Massachusetts Institute of Technology), Matus Telgarsky (University of Illinois, Urbana-Champaign)
Probability, Geometry, and Computation in High Dimensions Boot Camp
Aug. 19 – Aug. 28, 2020
Program: Probability, Geometry, and Computation in High Dimensions
Theory of Reinforcement Learning Boot Camp
Aug. 31 – Sep. 4, 2020
Program: Theory of Reinforcement Learning

Organizers:

Csaba Szepesvari (DeepMind & University of Alberta; chair), Emma Brunskill (Stanford University), Sébastien Bubeck (MSR), Alan Malek (DeepMind), Sean Meyn (University of Florida), Ambuj Tewari (University of Michigan), Mengdi Wang (Princeton)
Geometry of Polynomials Reunion
Sep. 8 – Sep. 11, 2020
Program: Geometry of Polynomials

Organizers:

Shayan Oveis Gharan (University of Washington; co-chair), Nikhil Srivastava (UC Berkeley; co-chair), Leonid Gurvits (City University of New York), Pablo Parrilo (Massachusetts Institute of Technology), Alistair Sinclair (UC Berkeley)
Computational Phase Transitions
Sep. 21 – Sep. 25, 2020
Program: Probability, Geometry, and Computation in High Dimensions
Deep Reinforcement Learning
Sep. 28 – Oct. 2, 2020
Program: Theory of Reinforcement Learning

Organizers:

Lihong Li (Google Brain; chair), Marc G. Bellemare (Google Brain)
Concentration of Measure Phenomena
Oct. 19 – Oct. 23, 2020
Program: Probability, Geometry, and Computation in High Dimensions
Mathematics of Online Decision Making
Oct. 26 – Oct. 30, 2020
Program: Theory of Reinforcement Learning

Organizers:

Shipra Agrawal (Columbia University; chair), Sébastien Bubeck (MSR), Alan Malek (DeepMind)
Learning and Testing in High Dimensions
Nov. 16 – Nov. 20, 2020
Program: Probability, Geometry, and Computation in High Dimensions
Reinforcement Learning from Batch Data and Simulation
Nov. 30 – Dec. 4, 2020
Program: Theory of Reinforcement Learning

Organizers:

Mengdi Wang (Princeton; chair), Emma Brunskill (Stanford University), Sean Meyn (University of Florida)
Theoretical Foundations of Computer Systems Boot Camp
Jan. 25 – Jan. 29, 2021
Program: Theoretical Foundations of Computer Systems
Satisfiability: Theory, Practice, and Beyond Boot Camp
Feb. 1 – Feb. 5, 2021
Program: Satisfiability: Theory, Practice, and Beyond
Theoretical Foundations of SAT/SMT Solving
Feb. 22 – Feb. 26, 2021
Program: Theoretical Foundations of Computer Systems, Satisfiability: Theory, Practice, and Beyond
Beyond Satisfiability
Mar. 15 – Mar. 19, 2021
Program: Satisfiability: Theory, Practice, and Beyond
Synthesis of Models and Systems
Mar. 22 – Mar. 25, 2021
Program: Theoretical Foundations of Computer Systems
50 Years of Satisfiability: The Centrality of SAT in the Theory of Computing
Apr. 12 – Apr. 16, 2021
Program: Satisfiability: Theory, Practice, and Beyond
Games and Equilibria in System Design and Analysis
Apr. 26 – Apr. 30, 2021
Program: Theoretical Foundations of Computer Systems
Expressiveness versus Efficiency
May 3 – May 7, 2021
Program: Satisfiability: Theory, Practice, and Beyond
Statistics in the Big Data Era
Jun. 2 – Jun. 4, 2021
Interpretable Machine Learning in Natural and Social Sciences
Jun. 28 – Jul. 1, 2021
Program: Summer Cluster: Interpretable Machine Learning

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