ADSI Summer Workshop: Algorithmic Foundations of Learning and Control

Hosted by the Algorithmic Foundations of Data Science Institute
University of Washington

Jointly organized with IFDS, University of Wisconsin - Madison


August 19-21, 2019


Bill & Melinda Gates Center, University of Washington

Invited Speakers

Emo Todorov
University of Washington
Pablo Parrilo
Massachusetts Institute of Technology
Alekh Agarwal
Microsoft Research
Sample-Efficient Exploration in Reinforcement Learning with Rich Observations
Csaba Szepesvári
University of Alberta
Politex - Towards Stable and Efficient Reinforcement Learning Algorithms that Generalize
Mengdi Wang
Princeton University
Reinforcement Learning From Small Data in Feature Space
Necmiye Ozay
University of Michigan
Non-Asymptotic Analysis of a Classical System Identification Algorithm
Ben Recht
University of California, Berkeley
Characterizing Uncertainty in Perception for Control
Yishay Mansour
Tel Aviv University
Linear Quadratic Control and Online Learning
Emma Brunskill
Stanford University
Batch / Counterfactual Reinforcement Learning
Yinyu Ye
Stanford University
Further Developments on Online Linear Programming and Learning
Daniel Russo
Columbia University
Exploration via Randomized Value Functions
Byron Boots
Georgia Institute of Technology
An Online Learning Approach to Model Predictive Control
Vikash Kumar
Google Brain


Live Stream

Lectures will be held in Zillow Commons, 4th floor of Gates Center

Discussion sessions will be held in G04, ground floor of Gates Center

August 19

9:00-9:45 Lecture: Yinyu Ye
9:45-10:30 Lecture: Mengdi Wang
10:30-11:00 Break
11:00-11:45 Lecture: Ben Recht
11:45-1:30 Lunch
1:30-2:15 Lecture: Alekh Agarwal
2:15-3:00 Lecture: Daniel Russo
3:00-3:30 Break
3:30-4:30 Discussion Session
4:30-6:30 Poster Session & Reception

August 20

9:00-9:45 Lecture: Yishay Mansour
9:45-10:30 Lecture: Emo Todorov
10:30-11:00 Break
11:00-11:45 Lecture: Emma Brunskill
11:45-1:30 Lunch
1:30-2:15 Lecture: Necmiye Ozay
2:15-3:00 Lecture: Pablo Parrilo
3:00-3:30 Break
3:30-4:30 Discussion Session

August 21

9:00-9:45 Lecture: Byron Boots
9:45-10:30 Lecture: Vikash Kumar
10:30-11:00 Break
11:00-11:45 Lecture: Csaba Szepesvári
11:45-1:30 Lunch


This workshop aims to bring together researchers with different backgrounds in computer science, control theory, statistics and math who are interested in bridging reinforcement learning, control theory, and statistical learning.
If you plan to attend, please do register. It is FREE. We request this as it helps us plan the event better, and to justify the importance of such events in our reports to NSF.

Registration Form

Organizers: Maryam Fazel (UW), Sham Kakade (UW), Kevin Jamieson (UW), Stephen Wright (Wisconsin)


Questions? Contact us!