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07/21/2023
JoinGym: An Efficient Query Optimization Environment for Reinforcement Learning
In this paper, we present JoinGym, an efficient and lightweight query op...
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05/25/2023
The Benefits of Being Distributional: Small-Loss Bounds for Reinforcement Learning
While distributional reinforcement learning (RL) has demonstrated empiri...
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02/07/2023
Near-Minimax-Optimal Risk-Sensitive Reinforcement Learning with CVaR
In this paper, we study risk-sensitive Reinforcement Learning (RL), focu...
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07/12/2022
Learning Bellman Complete Representations for Offline Policy Evaluation
We study representation learning for Offline Reinforcement Learning (RL)...
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05/29/2022
Provable Benefits of Representational Transfer in Reinforcement Learning
We study the problem of representational transfer in RL, where an agent ...
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02/19/2022
Doubly Robust Distributionally Robust Off-Policy Evaluation and Learning
Off-policy evaluation and learning (OPE/L) use offline observational dat...
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05/14/2021
Partitioned Active Learning for Heterogeneous Systems
Cost-effective and high-precision surrogate modeling is a cornerstone of...
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12/19/2020
Scalable and Provably Accurate Algorithms for Differentially Private Distributed Decision Tree Learning
This paper introduces the first provably accurate algorithms for differe...
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12/12/2020
NP-ODE: Neural Process Aided Ordinary Differential Equations for Uncertainty Quantification of Finite Element Analysis
Finite element analysis (FEA) has been widely used to generate simulatio...
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05/31/2018
Respond-CAM: Analyzing Deep Models for 3D Imaging Data by Visualizations
The convolutional neural network (CNN) has become a powerful tool for va...
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05/16/2018
