Wen Sun

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Carnegie Mellon University

Member of Royal Irish Academy, Member of Academia Europaea, Foreign Member of Polish Academy of Sciences, Full Professor of Food and Biosystems Engineering at University College Dublin

Adaptive Federated Learning and Digital Twin for Industrial Internet of Things

Industrial Internet of Things (IoT) enables distributed intelligent serv...
10/25/2020 ∙ by Wen Sun, et al. ∙ 3 ∙ share

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Learning the Linear Quadratic Regulator from Nonlinear Observations

We introduce a new problem setting for continuous control called the LQR...
10/08/2020 ∙ by Zakaria Mhammedi, et al. ∙ 4 ∙ share

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PC-PG: Policy Cover Directed Exploration for Provable Policy Gradient Learning

Direct policy gradient methods for reinforcement learning are a successf...
07/16/2020 ∙ by Alekh Agarwal, et al. ∙ 0 ∙ share

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Information Theoretic Regret Bounds for Online Nonlinear Control

This work studies the problem of sequential control in an unknown, nonli...
06/22/2020 ∙ by Sham Kakade, et al. ∙ 14 ∙ share

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FLAMBE: Structural Complexity and Representation Learning of Low Rank MDPs

In order to deal with the curse of dimensionality in reinforcement learn...
06/18/2020 ∙ by Alekh Agarwal, et al. ∙ 7 ∙ share

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Provably Efficient Model-based Policy Adaptation

The high sample complexity of reinforcement learning challenges its use ...
06/14/2020 ∙ by Yuda Song, et al. ∙ 7 ∙ share

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Constrained episodic reinforcement learning in concave-convex and knapsack settings

We propose an algorithm for tabular episodic reinforcement learning with...
06/09/2020 ∙ by Kianté Brantley, et al. ∙ 8 ∙ share

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Arbitrary Style Transfer via Multi-Adaptation Network

Arbitrary style transfer is a significant topic with both research value...
05/27/2020 ∙ by Yingying Deng, et al. ∙ 4 ∙ share

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Exploration in Action Space

Parameter space exploration methods with black-box optimization have rec...
03/31/2020 ∙ by Anirudh Vemula, et al. ∙ 5 ∙ share

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Corruption Robust Exploration in Episodic Reinforcement Learning

We initiate the study of multi-stage episodic reinforcement learning und...
11/20/2019 ∙ by Thodoris Lykouris, et al. ∙ 12 ∙ share

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Policy Poisoning in Batch Reinforcement Learning and Control

We study a security threat to batch reinforcement learning and control w...
10/13/2019 ∙ by Yuzhe Ma, et al. ∙ 8 ∙ share

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Optimal Sketching for Kronecker Product Regression and Low Rank Approximation

We study the Kronecker product regression problem, in which the design m...
09/29/2019 ∙ by Huaian Diao, et al. ∙ 8 ∙ share

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Imitation Learning as f-Divergence Minimization

We address the problem of imitation learning with multi-modal demonstrat...
05/30/2019 ∙ by Liyiming Ke, et al. ∙ 9 ∙ share

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Provably Efficient Imitation Learning from Observation Alone

We study Imitation Learning (IL) from Observations alone (ILFO) in large...
05/27/2019 ∙ by Wen Sun, et al. ∙ 2 ∙ share

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Efficient Model-free Reinforcement Learning in Metric Spaces

Model-free Reinforcement Learning (RL) algorithms such as Q-learning [Wa...
05/01/2019 ∙ by Zhao Song, et al. ∙ 8 ∙ share

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Outcome-Driven Clustering of Acute Coronary Syndrome Patients using Multi-Task Neural Network with Attention

Cluster analysis aims at separating patients into phenotypically heterog...
03/01/2019 ∙ by Eryu Xia, et al. ∙ 4 ∙ share

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Contrasting Exploration in Parameter and Action Space: A Zeroth-Order Optimization Perspective

Black-box optimizers that explore in parameter space have often been sho...
01/31/2019 ∙ by Anirudh Vemula, et al. ∙ 4 ∙ share

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Model-Based Reinforcement Learning in Contextual Decision Processes

We study the sample complexity of model-based reinforcement learning in ...
11/21/2018 ∙ by Wen Sun, et al. ∙ 12 ∙ share

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Contextual Memory Trees

We design and study a Contextual Memory Tree (CMT), a learning memory co...
07/17/2018 ∙ by Wen Sun, et al. ∙ 6 ∙ share

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Truncated Horizon Policy Search: Combining Reinforcement Learning & Imitation Learning

In this paper, we propose to combine imitation and reinforcement learnin...
05/29/2018 ∙ by Wen Sun, et al. ∙ 0 ∙ share

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Dual Policy Iteration

Recently, a novel class of Approximate Policy Iteration (API) algorithms...
05/28/2018 ∙ by Wen Sun, et al. ∙ 0 ∙ share

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Recurrent Predictive State Policy Networks

We introduce Recurrent Predictive State Policy (RPSP) networks, a recurr...
03/05/2018 ∙ by Ahmed Hefny, et al. ∙ 0 ∙ share

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Sketching for Kronecker Product Regression and P-splines

TensorSketch is an oblivious linear sketch introduced in Pagh'13 and lat...
12/27/2017 ∙ by Huaian Diao, et al. ∙ 0 ∙ share

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Predictive-State Decoders: Encoding the Future into Recurrent Networks

Recurrent neural networks (RNNs) are a vital modeling technique that rel...
09/25/2017 ∙ by Arun Venkatraman, et al. ∙ 0 ∙ share

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Risk-Aware Algorithms for Adversarial Contextual Bandits

In this work we consider adversarial contextual bandits with risk constr...
10/17/2016 ∙ by Wen Sun, et al. ∙ 0 ∙ share

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Wen Sun

Featured Co-authors

Yan Zhang

Jian Li

Byron Boots

David P. Woodruff

Zhao Song

Lu Wang

Akshay Krishnamurthy

Alekh Agarwal

Feiyue Huang

Alexander Rakhlin

John Langford

Adaptive Federated Learning and Digital Twin for Industrial Internet of Things

Learning the Linear Quadratic Regulator from Nonlinear Observations

PC-PG: Policy Cover Directed Exploration for Provable Policy Gradient Learning

Information Theoretic Regret Bounds for Online Nonlinear Control

FLAMBE: Structural Complexity and Representation Learning of Low Rank MDPs

Provably Efficient Model-based Policy Adaptation

Constrained episodic reinforcement learning in concave-convex and knapsack settings

Arbitrary Style Transfer via Multi-Adaptation Network

Exploration in Action Space

Corruption Robust Exploration in Episodic Reinforcement Learning

Policy Poisoning in Batch Reinforcement Learning and Control

Optimal Sketching for Kronecker Product Regression and Low Rank Approximation

Imitation Learning as f-Divergence Minimization

Provably Efficient Imitation Learning from Observation Alone

Efficient Model-free Reinforcement Learning in Metric Spaces

Outcome-Driven Clustering of Acute Coronary Syndrome Patients using Multi-Task Neural Network with Attention

Contrasting Exploration in Parameter and Action Space: A Zeroth-Order Optimization Perspective

Model-Based Reinforcement Learning in Contextual Decision Processes

Contextual Memory Trees

Truncated Horizon Policy Search: Combining Reinforcement Learning & Imitation Learning

Dual Policy Iteration

Recurrent Predictive State Policy Networks

Sketching for Kronecker Product Regression and P-splines

Predictive-State Decoders: Encoding the Future into Recurrent Networks

Risk-Aware Algorithms for Adversarial Contextual Bandits