Reinforcement Learning From Small Data in Feature Space - 2019 ADSI Summer Workshop

Explore reinforcement learning techniques for small datasets in feature space through this insightful lecture presented by Mengdi Wang from Princeton University. Delivered at the ADSI Summer Workshop on Algorithmic Foundations of Learning and Control, hosted by the Paul G. Allen School of Computer Science & Engineering at the University of Washington, this 44-minute talk delves into cutting-edge approaches for maximizing learning efficiency with limited data. Gain valuable insights into the intersection of reinforcement learning, feature space analysis, and data optimization as Wang shares her expertise in this rapidly evolving field of artificial intelligence and machine learning.