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06/23/2023
Active Coverage for PAC Reinforcement Learning
Collecting and leveraging data with good coverage properties plays a cru...
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02/07/2023
Layered State Discovery for Incremental Autonomous Exploration
We study the autonomous exploration (AX) problem proposed by Lim Aue...
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12/19/2022
On the Complexity of Representation Learning in Contextual Linear Bandits
In contextual linear bandits, the reward function is assumed to be a lin...
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10/24/2022
Scalable Representation Learning in Linear Contextual Bandits with Constant Regret Guarantees
We study the problem of representation learning in stochastic contextual...
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10/10/2022
Reaching Goals is Hard: Settling the Sample Complexity of the Stochastic Shortest Path
We study the sample complexity of learning an ϵ-optimal policy in the St...
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07/12/2022
Optimistic PAC Reinforcement Learning: the Instance-Dependent View
Optimistic algorithms have been extensively studied for regret minimizat...
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05/22/2022
On Elimination Strategies for Bandit Fixed-Confidence Identification
Elimination algorithms for bandit identification, which prune the plausi...
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03/17/2022
Near Instance-Optimal PAC Reinforcement Learning for Deterministic MDPs
In probably approximately correct (PAC) reinforcement learning (RL), an ...
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11/02/2021
Dealing With Misspecification In Fixed-Confidence Linear Top-m Identification
We study the problem of the identification of m arms with largest means ...
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10/27/2021
Reinforcement Learning in Linear MDPs: Constant Regret and Representation Selection
We study the role of the representation of state-action value functions ...
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06/24/2021
A Fully Problem-Dependent Regret Lower Bound for Finite-Horizon MDPs
We derive a novel asymptotic problem-dependent lower-bound for regret mi...
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05/18/2021
Meta-Reinforcement Learning by Tracking Task Non-stationarity
Many real-world domains are subject to a structured non-stationarity whi...
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04/08/2021
Leveraging Good Representations in Linear Contextual Bandits
The linear contextual bandit literature is mostly focused on the design ...
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10/23/2020
An Asymptotically Optimal Primal-Dual Incremental Algorithm for Contextual Linear Bandits
In the contextual linear bandit setting, algorithms built on the optimis...
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07/01/2020
Sequential Transfer in Reinforcement Learning with a Generative Model
We are interested in how to design reinforcement learning agents that pr...
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05/23/2020
A Novel Confidence-Based Algorithm for Structured Bandits
We study finite-armed stochastic bandits where the rewards of each arm m...
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09/09/2019
Gradient-Aware Model-based Policy Search
Traditional model-based reinforcement learning approaches learn a model ...
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07/17/2019
Feature Selection via Mutual Information: New Theoretical Insights
Mutual information has been successfully adopted in filter feature-selec...
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05/28/2018