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Welcome to the website for the Stanford RL (Reinforcement Learning) Forum.

We hope to develop a growing community of researchers in both industry and academia that are interested in reinforcement learning. With connections to control theory, operations research, computer science, statistics, and many more fields this may include a lot of people!

Details of the upcoming talks will be posted in the talks section. Also, subscribe to the mailing list here.
The RL Forum is sponsored by the Stanford Computer Forum.
RL Forum talks:

Reinforcement Learning, Bit by Bit (Xiuyuan (Lucy) Lu)

Lecture 1: 9:30 AM - 10:30 AM (PT), April 20th (Tuesday)
Lecture 2: 10:30 AM - 11:30 AM (PT), April 23rd (Friday)
(Lecture 1 Recording)

(Lecture 2 Recording)

Provable Model-based Nonlinear Bandit and Reinforcement Learning (Tengyu Ma)

2:30 PM - 4:00 PM (PT), April 15th (Thursday) Online
Diffusion Asymptotics for Sequential Experiments (Kuang Xu) 1:00 PM - 2:00 PM (PT), March 23rd (Tuesday) Online
Lectures on Information Directed Sampling (Tor Lattimore) 10:00 AM - 11:00 AM, Jan 11 & 13, 2021 (Monday & Wednesday)

(Lecture 1 Recording)

(Lecture 2 Recording)

Temporal Abstraction in Reinforcement Learning with the Successor Representation (Marlos Machado 2:00 PM - 3:00 PM, Feb 25, 2020 (Tuesday) Packard 202
From Reinforcement Learning to Stochastic Optimization: A Universal Framework for Sequential Decision Analytics (Warren Powell) 4:30 PM - 5:30 PM, Jan 29, 2020 (Wednesday) Shriram 262
Representation, Modeling, and Optimization in Reinforcement Learning (Sham Kakade) 4:30 PM - 5:30 PM, Jan 22, 2020 (Wednesday) 200 - 034
Do Deep Generative Models Know What They Don't Know? (Balaji Lakshminarayanan) 4:00 PM - 5:00 PM,  May 28, 2019 (Tuesday) Packard 101
Reinforcement Learning and Optimal Control: An Overview (Dimitri P. Bertsekas) 4:00 PM - 5:00 PM, March 4, 2019 (Monday) Packard 101
4:15 PM - 5:15 PM, Nov 13, 2018 (Tuesday) Packard 202
Is Q-learning Provably Efficient? (Chi Jin) 3:15 PM - 4:15 PM, Oct 12, 2018 (Friday)  Packard 202



Organising Members

Professor of Electrical Engineering, Management Science and Engineering, and, by courtesy, Computer Science
Adithya M. Devraj
Postdoc in Electrical Engineering
Shi Dong
Ph.D. Candidate in Electrical Engineering
Vikranth Reddy Dwaracherla
Ph.D. Candidate in Electrical Engineering   


Reinforcement Learning, Bit by Bit

Xiuyuan (Lucy) Lu
Research Scientist,
DeepMind, Mountain View

Location: Online

Contact us

If you have any comments, questions or suggestions please feel free to get in touch with an organizing member.

For organizational or site-specific problems please reach out to sdong15 or vikranth "at" stanford "dot" edu.

You can subscribe to the mailing list here.

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