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08/17/2023
Synthesizing Physically Plausible Human Motions in 3D Scenes
Synthesizing physically plausible human motions in 3D scenes is a challe...
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05/31/2023
Offline Meta Reinforcement Learning with In-Distribution Online Adaptation
Recent offline meta-reinforcement learning (meta-RL) methods typically u...
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03/06/2023
Cost Sharing under Private Valuation and Connection Control
We consider a cost sharing problem on a weighted undirected graph, where...
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02/25/2023
Provably Efficient Gauss-Newton Temporal Difference Learning Method with Function Approximation
In this paper, based on the spirit of Fitted Q-Iteration (FQI), we propo...
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07/13/2022
A Near-Optimal Primal-Dual Method for Off-Policy Learning in CMDP
As an important framework for safe Reinforcement Learning, the Constrain...
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01/16/2022
Cost Sharing for Connectivity with Budget
We consider a cost sharing problem to connect all nodes in a weighted un...
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06/15/2021
On the Sample Complexity and Metastability of Heavy-tailed Policy Search in Continuous Control
Reinforcement learning is a framework for interactive decision-making wi...
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05/29/2021
MARL with General Utilities via Decentralized Shadow Reward Actor-Critic
We posit a new mechanism for cooperation in multi-agent reinforcement le...
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03/06/2021
Zero-sum risk-sensitive continuous-time stochastic games with unbounded payoff and transition rates and Borel spaces
We study a finite-horizon two-person zero-sum risk-sensitive stochastic ...
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02/17/2021
On the Convergence and Sample Efficiency of Variance-Reduced Policy Gradient Method
Policy gradient gives rise to a rich class of reinforcement learning (RL...
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07/04/2020
Variational Policy Gradient Method for Reinforcement Learning with General Utilities
In recent years, reinforcement learning (RL) systems with general goals ...
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06/20/2020
On the Divergence of Decentralized Non-Convex Optimization
We study a generic class of decentralized algorithms in which N agents j...
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02/27/2020
Cautious Reinforcement Learning via Distributional Risk in the Dual Domain
We study the estimation of risk-sensitive policies in reinforcement lear...
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08/29/2019
Multi-Level Composite Stochastic Optimization via Nested Variance Reduction
We consider multi-level composite optimization problems where each mappi...
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06/24/2019
A Stochastic Composite Gradient Method with Incremental Variance Reduction
We consider the problem of minimizing the composition of a smooth (nonco...
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11/21/2018
SuperNeurons: FFT-based Gradient Sparsification in the Distributed Training of Deep Neural Networks
The performance and efficiency of distributed training of Deep Neural Ne...
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02/06/2018
Highly accurate model for prediction of lung nodule malignancy with CT scans
Computed tomography (CT) examinations are commonly used to predict lung ...
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10/05/2017