MAKING NON-STOCHASTIC CONTROL (ALMOST) AS EASY AS STOCHASTIC

von Simchowitz, Max
Veröffentlicht in NeurIPS (34. : 2020 : Online) 34th Conference on Neural Information Processing Systems (NeurIPS 2020) ; Volume 22 of 27 (2021)

Efficient and Near-Optimal Smoothed Online Learning for Generalized Linear Functions

von Block, Adam
Veröffentlicht in NeurIPS (36. : 2022 : New Orleans, La.; Online) 36th Conference on Neural Information Processing Systems (NeurIPS 2022 ; Volume 10 of 50 (2023)

NON-ASYMPTOTIC GAP-DEPENDENT REGRET BOUNDS FOR TABULAR MDTPS

von Simchowitz, Max
Veröffentlicht in NeurIPS (33. : 2019 : Vancouver, British Columbia) 32nd Conference on Neural Information Processing Systems (NeurIPS 2019) ; Volume 2 of 20 (2020)

TASK-OPTIMAL EXPLORATION IN LINEAR DYNAMICAL SYSTEMS

von WAGENMAKER, ANDREW
Veröffentlicht in International Conference on Machine Learning (38. : 2021 : Online) International Conference on Machine Learning (ICML 2021 ; Part 14 of 16 (2022)

Stabilizing Dynamical Systems via Policy Gradient Methods

von Perdomo, Juan
Veröffentlicht in NeurIPS (35. : 2021 : Online) 35th Conference on Neural Information Processing Systems (NeurIPS 2021) ; Volume 35 of 36 (2022)

Online Control of Unknown Time-Varying Dynamical Systems

von Minasyan, Edgar
Veröffentlicht in NeurIPS (35. : 2021 : Online) 35th Conference on Neural Information Processing Systems (NeurIPS 2021) ; Volume 19 of 36 (2022)

REWARD-FREE EXPLORATION FOR REINFORCEMENT LEARNING

von Jin, Chi
Veröffentlicht in International Conference on Machine Learning (37. : 2020 : Online) 37th International Conference on Machine Learning (ICML 2020) ; Part 7 of 15 (2021)

Do Differentiable Simulators Give Better Policy Gradients?

von Suh, Hyung Ju
Veröffentlicht in International Conference on Machine Learning (39. : 2022 : Baltimore, Md.; Online) International Conference on Machine Learning (ICML 2022) ; Part 35 of 33 (2023)

Globally Convergent Policy Search for Output Estimation

von Umenberger, Jack
Veröffentlicht in NeurIPS (36. : 2022 : New Orleans, La.; Online) 36th Conference on Neural Information Processing Systems (NeurIPS 2022 ; Volume 30 of 50 (2023)

First-Order Regret in Reinforcement Learning with Linear Function Approximation: A Robust Estimation Approach

von Wagenmaker, Andrew J.
Veröffentlicht in International Conference on Machine Learning (39. : 2022 : Baltimore, Md.; Online) International Conference on Machine Learning (ICML 2022) ; Part 27 of 33 (2023)

Reward-Free RL is No Harder than Reward-Aware RL in Linear Markov Decision Processes

von Wagenmaker, Andrew J.
Veröffentlicht in International Conference on Machine Learning (39. : 2022 : Baltimore, Md.; Online) International Conference on Machine Learning (ICML 2022) ; Part 27 of 33 (2023)

CONSTRAINED EPISODIC REINFORCEMENT LEARNING IN CONCAVE-CONVEX AND KNAPSACK SETTINGS

von Brantley, Kiante
Veröffentlicht in NeurIPS (34. : 2020 : Online) 34th Conference on Neural Information Processing Systems (NeurIPS 2020) ; Volume 20 of 27 (2021)

BALANCING COMPETING OBJECTIVES WITH NOISY DATA: SCORE-BASED CLASSIFIERS FOR WELFARE-AWARE MACHINE LEARNING

von Rolf, Esther
Veröffentlicht in International Conference on Machine Learning (37. : 2020 : Online) 37th International Conference on Machine Learning (ICML 2020) ; Part 11 of 15 (2021)

Bayesian decision-making under misspecified priors with applications to meta-learning

von Simchowitz, Max
Veröffentlicht in NeurIPS (35. : 2021 : Online) 35th Conference on Neural Information Processing Systems (NeurIPS 2021) ; Volume 32 of 36 (2022)

LEARNING THE LINEAR QUADRATIC REGULATOR FROM NONLINEAR OBSERVATIONS

von Mhammedi, Zakaria
Veröffentlicht in NeurIPS (34. : 2020 : Online) 34th Conference on Neural Information Processing Systems (NeurIPS 2020) ; Volume 18 of 27 (2021)