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05/22/2023
Regularization and Variance-Weighted Regression Achieves Minimax Optimality in Linear MDPs: Theory and Practice
Mirror descent value iteration (MDVI), an abstraction of Kullback-Leible...
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05/19/2023
Non-stationary Projection-free Online Learning with Dynamic and Adaptive Regret Guarantees
Projection-free online learning has drawn increasing interest due to its...
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04/29/2023
Semi-Infinitely Constrained Markov Decision Processes and Efficient Reinforcement Learning
We propose a novel generalization of constrained Markov decision process...
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02/02/2023
Avoiding Model Estimation in Robust Markov Decision Processes with a Generative Model
Robust Markov Decision Processes (MDPs) are getting more attention for l...
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09/12/2022
Statistical Estimation of Confounded Linear MDPs: An Instrumental Variable Approach
In an Markov decision process (MDP), unobservable confounders may exist ...
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05/27/2022
KL-Entropy-Regularized RL with a Generative Model is Minimax Optimal
In this work, we consider and analyze the sample complexity of model-fre...
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05/18/2022
Pluralistic Image Completion with Probabilistic Mixture-of-Experts
Pluralistic image completion focuses on generating both visually realist...
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04/06/2022
Federated Reinforcement Learning with Environment Heterogeneity
We study a Federated Reinforcement Learning (FedRL) problem in which n a...
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01/08/2022
AnomMAN: Detect Anomaly on Multi-view Attributed Networks
Anomaly detection on attributed networks is widely used in web shopping,...
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05/09/2021
Non-asymptotic Performances of Robust Markov Decision Processes
In this paper, we study the non-asymptotic performance of optimal policy...
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10/21/2019
Communication Efficient Decentralized Training with Multiple Local Updates
Communication efficiency plays a significant role in decentralized optim...
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07/04/2019
On the Convergence of FedAvg on Non-IID Data
Federated learning enables a large amount of edge computing devices to l...
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03/02/2019