Internal Program Activities Breadcrumb Home Programs & Events Internal Activities Upcoming Past View Events by Program - All - View Events by Program No Internal Activities yet. View Events by Program - All -Theory of Reinforcement LearningProbability, Geometry, and Computation in High Dimensions View Events by Program Reading Group: Deep RL and Function Approximation Reading Group: Deep RL and Function Approximation Theory of Reinforcement Learning Computational/Statistical Gaps for Learning Neural Networks Computational/Statistical Gaps for Learning Neural Networks Probability, Geometry, and Computation in High Dimensions Adam Klivans (University of Texas, Austin) Reading Group: Causality and Econometrics Reading Group: Causality and Econometrics Theory of Reinforcement Learning Open Problem Discussion Open Problem Discussion Theory of Reinforcement Learning Reading Group: Deep RL and Function Approximation Reading Group: Deep RL and Function Approximation Theory of Reinforcement Learning Is Reinforcement Learning More Difficult Than Bandits? A Near-optimal Algorithm Escaping the Curse of Horizon Is Reinforcement Learning More Difficult Than Bandits? A Near-optimal Algorithm Escaping the Curse of Horizon Theory of Reinforcement Learning Simon S. Du (University of Washington) Reading Group: Causality and Econometrics Reading Group: Causality and Econometrics Theory of Reinforcement Learning Fellows Talk - Christina Yu Fellows Talk - Christina Yu Probability, Geometry, and Computation in High Dimensions Christina Yu (Cornell University) Open Problem Discussion Open Problem Discussion Theory of Reinforcement Learning Reading Group: Deep RL and Function Approximation Reading Group: Deep RL and Function Approximation Theory of Reinforcement Learning Pagination First page First Previous page Previous Page 79 Page 80 Current page 81 Page 82 Page 83 Next page Next Last page Last
