Seminar Schedule
July 8th – July 11th, 2022
8:00pm – 5:00am EST
From Statistics to Artificial Intelligence – Reinforcement Learning Conference
Detailed Schedule: www.arlseminar.com/from-statistics-to-artificial-intelligence-reinforcement-learning/
April 13th, 2022
9:00am – 10:00am EST
S. Kevin Zhou, University of Science and Technology of China (USTC)
Traits and Trends of AI in Medical Imaging
Mar 9th, 2022
8:00pm – 9:00pm EST
Andrea Zanette, University of California at Berkeley
Discussant: Xiaocheng Tang, DiDi Labs
Provable Benefits of Actor-Critic Methods for Offline Reinforcement Learning
Feb 23rd, 2022
9:00am – 10:00am EST
Lerrel Pinto, New York University
Xinrun Wang, Nanyang Technological University, Singapore
Rethinking Representations for Robotics
Feb 3rd, 2022
8:00pm – 9:00pm EST
Bin Dong, Peking University
Xin Wang, Keya Medical
Some Applications of Deep Reinforcement Learning to Imaging and Numerical PDEs
Jan 25th, 2022
8:30am – 10:00am EST
Siwei Lyu, University at Buffalo, State University of New York
Xin Wang, Keya Medical
Image to image transform (I2IT) with deep reinforcement learning
Jan 13th, 2022
9:00am – 10:00am EST
Chengchun Shi, London School of Economics and Political Science
Statistical inference in reinforcement learning
Discussion Leader: Zhengling Qi, George Washington University
Dec 1st, 2021
8:15am – 9:15am EST
Jiayu Zhou, Michigan State University
Advancements in Artificial Intelligence for Neurodegenerative Diseases
Discussion Leader: Fei Wang, Cornell University
Nov 11th, 2021
8:30am – 9:30am EST
Jim Dai, Cornell University & Chinese University of Hong Kong, Shenzhen
Scalable Deep Reinforcement Learning for Ride-Hailing
Oct 28th, 2021
10:00am – 11:00am EST
Linglong Kong, University of Alberta
Damped Anderson Mixing for Deep Reinforcement Learning and Applications
May 26th, 2021
11:30am – 12:00am EST
Houssam Nassif, Amazon
Solving Inverse Reinforcement Learning, Bootstrapping Bandits
May 26th, 2021
11:30am – 12:30pm EST
Zhaoran Wang, Northwestern University
Is Pessimism Provably Efficient for Offline RL?
May 26th, 2021
10:30am – 11:00am EST
Zhuoran Yang, Princeton University
On Function Approximation in Reinforcement Learning: Optimism in the Face of Large State Space
May 13th, 2021
10:30pm – 11:30pm EST
Guanjie Zheng, Shanghai Jiao Tong University
Improving Urban Traffic Signal Control via Reinforcement Learning
April 29th, 2021
9:00pm – 10:00pm EST
Keith Ross, New York University Shanghai, United States
Recent Advances in Sample Efficient DRL
April 15th, 2021
9:00pm – 10:00pm EST
Mengdi Wang, Princeton University, United States
Compressive state representation learning towards small-data RL applications
April 1st, 2021
9:00pm – 10:00pm EST
Wenbin Lu, North Carolina State University, United States
Jump Q-Learning for Optimal Interval-Values Treatment Decision Rule
Discussion Leader: Guanhua, Chen, University of Wisconsin-Madison, United States
March 18th, 2021
8:30pm – 9:30pm EST
Dong Zhang, Western University, Canada
Deep reinforcement learning in medical object detection and segmentation
Discussion Leader: Shuo Li, Western University, Canada
March 4th, 2021
8:00pm – 9:00pm EST
Peng Wei, George Washington University
Deep Multi-Agent Reinforcement Learning for Autonomous Urban Air Mobility
February 18th, 2021
8:00pm – 9:00pm EST
Zhiyuan Liu, Southeast University, Nanjing China
Urban Transport Simulation Using Reinforcement Learning
Discussion Leader: Cheng Lyu, Southeast University, Nanjing China
January 28th, 2021
8:00pm – 9:00pm EST
Yuxi Li, author of the 150 pages Deep Reinforcement Learning: An Overview
Reinforcement Learning Applications
Discussion Leader: Lihang Ying, president of Alberta AI Association
January 14th, 2021
8:00pm – 9:00pm EST
Yanhua Li, Worcester Polytechnic Institute (WPI)
Decision Analysis from Human-Generated Spatial-Temporal Data
Discussion Leader: Haipeng Chen, Harvard University
December 16th, 2020
8:00pm – 9:00pm EST
Liam Paull, l’Université de Montréal
Training Robotics in Simulators
December 3rd, 2020
8:00pm – 9:00pm EST
Nick Rhinehart, University of California, Berkeley
Jointly Forecasting and Controlling Behavior by Learning From High-Dimensional Data
November 19th, 2020
10:00am – 11:00am EST
Nathan Kallus, Cornell University
Statistically Efficient Offline Reinforcement Learning
Discussion Leader: Chengchun Shi, London School of Economics and Political Science
November 5th, 2020
10:00am – 11:00am EST
Eric Laber, NC State University
Partially observable Markov Decision Processes as a Model for Chronic Illness
October 21st, 2020
11:00am – 12:00pm EST
Yansheng Wang, Beihang University & Fanyou Wu, Purdue University
KDD Cup 2020 RL Track Winners Presentation
October 7th, 2020
11:00am – 12:00pm EST
Tony Qin, DiDi AI Labs
Deep Reinforcement Learning in a Ride-sharing Marketplace
September 24th, 2020
11:00am – 12:00pm EST
Michael R. Kosorok, University of North Carolina at Chapel Hill
Off-Policy Reinforcement Learning for Estimation of Optimal Treatment Regime
August 27th, 2020
10:00am – 11:25am EST
Bo An, Nanyang Technological University
Reinforcement Learning in Competitive Environment
Susan Murphy, Harvard University
Intelligent Poolin: Practical Thompson Sampling for mHealth