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 Efficient Optimistic Exploration in Linear-Quadratic Regulators via Lagrangian Relaxation Efficient Optimistic Exploration in Linear-Quadratic Regulators via Lagrangian Relaxation Theory of Reinforcement Learning Marc Abeille (Criteo) Reading Group: Causality and Econometrics Reading Group: Causality and Econometrics Theory of Reinforcement Learning Fellows Talk - Tselil Schramm & Zhuoran Yang Fellows Talk - Tselil Schramm & Zhuoran Yang Probability, Geometry, and Computation in High Dimensions Tselil Schramm (Stanford University); Zhuoran Yang (Princeton 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 On (Non-Traditional) Costs and Potentials On (Non-Traditional) Costs and Potentials Probability, Geometry, and Computation in High Dimensions Shiri Artstein (Tel-Aviv University) 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 Robustly Learning Mixtures of (Clusterable) Gaussians via the SoS Proofs to Algorithms Method Robustly Learning Mixtures of (Clusterable) Gaussians via the SoS Proofs to Algorithms Method Probability, Geometry, and Computation in High Dimensions Sam Hopkins, UC Berkeley Pagination First page First Previous page Previous Page 82 Page 83 Current page 84 Page 85 Page 86 Next page Next Last page Last
