BeNeRL Seminar: Qiyang Li on Efficient Online Exploration
Join Qiyang Li’s BeNeRL Seminar on May 8 to learn about leveraging offline data for efficient online exploration in reinforcement learning.
Join the BeNeRL Reinforcement Learning Seminar on May 8, 16.00-17.00 (CET) as Qiyang Li from UC Berkeley presents ‘Leveraging unlabeled task-agnostic offline data for efficient online exploration’.
- Speaker: Qiyang Li (https://colinqiyangli.github.io/)
- Date: May 8, 16.00-17.00 (CET)
- Zoom Link: Join Seminar
Qiyang Li’s research focuses on using offline data to accelerate exploration for task-specific online learning, achieving significant exploration speedup in simulated robotic benchmarks.
Tags: Reinforcement Learning, BeNeRL Seminar, Qiyang Li, UC Berkeley, Online Exploration, RL Research, AI/ML