On instance-dependent bounds for offline reinforcement learning with linear function approximation
Sample-efficient offline reinforcement learning (RL) with linear function approximation has
been studied extensively recently. Much of the prior work has yielded instance-independent …
been studied extensively recently. Much of the prior work has yielded instance-independent …
On instance-dependent bounds for offline reinforcement learning with linear function approximation
T Nguyen-Tang, M Yin, S Gupta, S Venkatesh… - Proceedings of the …, 2023 - dl.acm.org
Sample-efficient offline reinforcement learning (RL) with linear function approximation has
been studied extensively recently. Much of the prior work has yielded instance-independent …
been studied extensively recently. Much of the prior work has yielded instance-independent …
On Instance-Dependent Bounds for Offline Reinforcement Learning with Linear Function Approximation
T Nguyen-Tang, M Yin, S Gupta, S Venkatesh… - arXiv preprint arXiv …, 2022 - arxiv.org
Sample-efficient offline reinforcement learning (RL) with linear function approximation has
recently been studied extensively. Much of prior work has yielded the minimax-optimal …
recently been studied extensively. Much of prior work has yielded the minimax-optimal …
[PDF][PDF] On Instance-Dependent Bounds for Offline Reinforcement Learning with Linear Function Approximation
T Nguyễn-Tang, M Yin, S Gupta, S Venkatesh… - Proceedings of the …, 2023 - par.nsf.gov
arXiv:2211.13208v2 [cs.LG] 27 Jan 2023 Page 1 On Instance-Dependent Bounds for Offline
Reinforcement Learning with Linear Function Approximation Thanh Nguyen-Tang1∗, Ming …
Reinforcement Learning with Linear Function Approximation Thanh Nguyen-Tang1∗, Ming …
On Instance-Dependent Bounds for Offline Reinforcement Learning with Linear Function Approximation
T Nguyen-Tang, M Yin, S Gupta, S Venkatesh, R Arora - 2023 - dro.deakin.edu.au
Sample-efficient offline reinforcement learning (RL) with linear function approximation has
been studied extensively recently. Much of the prior work has yielded instance-independent …
been studied extensively recently. Much of the prior work has yielded instance-independent …
On Instance-Dependent Bounds for Offline Reinforcement Learning with Linear Function Approximation
T Nguyen-Tang, M Yin, S Gupta, S Venkatesh… - arXiv e …, 2022 - ui.adsabs.harvard.edu
Sample-efficient offline reinforcement learning (RL) with linear function approximation has
recently been studied extensively. Much of prior work has yielded the minimax-optimal …
recently been studied extensively. Much of prior work has yielded the minimax-optimal …
On Instance-Dependent Bounds for Offline Reinforcement Learning with Linear Function Approximation
T Nguyen-Tang, M Yin, S Gupta, S Venkatesh, R Arora - 2023 - dro.deakin.edu.au
Sample-efficient offline reinforcement learning (RL) with linear function approximation has
been studied extensively recently. Much of the prior work has yielded instance-independent …
been studied extensively recently. Much of the prior work has yielded instance-independent …