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07/11/2023
Scaling Distributed Multi-task Reinforcement Learning with Experience Sharing
Recently, DARPA launched the ShELL program, which aims to explore how ex...
share
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06/01/2022
Provably Efficient Lifelong Reinforcement Learning with Linear Function Approximation
We study lifelong reinforcement learning (RL) in a regret minimization s...
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05/26/2022
Distributed Contextual Linear Bandits with Minimax Optimal Communication Cost
We study distributed contextual linear bandits with stochastic contexts,...
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06/11/2021
Safe Reinforcement Learning with Linear Function Approximation
Safety in reinforcement learning has become increasingly important in re...
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03/21/2021
UCB-based Algorithms for Multinomial Logistic Regression Bandits
Out of the rich family of generalized linear bandits, perhaps the most w...
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12/01/2020
Decentralized Multi-Agent Linear Bandits with Safety Constraints
We study decentralized stochastic linear bandits, where a network of N a...
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05/05/2020
Regret Bounds for Safe Gaussian Process Bandit Optimization
Many applications require a learner to make sequential decisions given u...
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11/06/2019
Safe Linear Thompson Sampling
The design and performance analysis of bandit algorithms in the presence...
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08/16/2019