Intersections between Control, Learning and Optimization

February 24 - 28, 2020

Schedule


Monday, February 24, 2020

Morning Session

8:00 - 8:55 Breakfast
8:55 - 9:00 Welcome & Opening Remarks
9:00 - 9:50
10:00 - 10:15 Break
10:15 - 11:05
Dimitri Bertsekas (Massachusetts Institute of Technology and Arizona State University)

Distributed and Multiagent Reinforcement Learning
PDF Presentation

 
11:15 - 11:30 Break
11:30 - 12:20
Csaba Szepesvari (University of Alberta)

Model misspecification in reinforcement learning

 
12:30 - 2:30 Lunch

Afternoon Session

2:30 - 3:20
3:30 - 4:00 Break
4:00 - 4:50
5:00 - 6:30 Reception (Hosted by IPAM) & Poster Session

Tuesday, February 25, 2020

Morning Session

8:00 - 9:00 Breakfast
9:00 - 9:50
Russell Tedrake (Massachusetts Institute of Technology)

From pixels to torques: output feedback for robotics

10:00 - 10:15 Break
10:15 - 11:05
Martin Riedmiller (DeepMind Technologies)

Learning Control from Minimal Prior Knowledge

11:15 - 11:30 Break
11:30 - 12:20
Ben Recht (University of California, Berkeley (UC Berkeley))

Trying to Make Sense of Control from Pixels

12:30 - 2:30 Lunch

Afternoon Session

2:30 - 3:20
3:30 - 4:00 Break
4:00 - 4:50

Wednesday, February 26, 2020

Morning Session

8:00 - 9:00 Breakfast
9:00 - 9:50
10:00 - 10:15 Break
10:15 - 11:05
Daniel Kuhn (École Polytechnique Fédérale de Lausanne (EPFL))

Wasserstein Distributionally Robust Optimization: Theory and Applications in Machine Learning
PDF Presentation

11:15 - 11:30 Break
11:30 - 12:20
12:30 - 2:30 Lunch

Afternoon Session

2:30 - 3:20
3:30 - 4:00 Break
4:00 - 4:50
Francesco Borrelli (University of California, Berkeley (UC Berkeley))

Sample-Based Learning Model Predictive Control


Thursday, February 27, 2020

Morning Session

8:00 - 9:00 Breakfast
9:00 - 9:50
Maryam Fazel (University of Washington)

Finite-sample System Identification: Optimal Rates and the Role of Regularization

10:00 - 10:15 Break
10:15 - 11:05
Richard Murray (California Institute of Technology)

Can We Really Use Machine Learning in Safety Critical Systems?

11:15 - 11:30 Break
11:30 - 12:20
Dorsa Sadigh (Stanford University)

Beyond Theory of Mind: Learning and Influencing Conventions in Multi-Agent Interactions

12:30 - 2:30 Lunch

Afternoon Session

2:30 - 3:20
James Rawlings (University of California, Santa Barbara (UCSB))

Industrial, large-scale model predictive control with deep neural networks

3:30 - 4:00 Break
4:00 - 4:50
Stephen Wright (University of Wisconsin-Madison)

Nonconvex optimization in matrix optimization and distributionally robust optimization


Friday, February 28, 2020

Morning Session

8:00 - 9:00 Breakfast
9:00 - 9:50 TBA
10:00 - 10:15 Break
10:15 - 11:05
Lieven Vandenberghe (University of California, Los Angeles (UCLA))

Bregman proximal methods for semidefinite optimization.

11:15 - 11:30 Break
11:30 - 12:20
12:30 Conclusion