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Optimal policy evaluation using kernel-based temporal difference methods


Sep 24, 2021
Yaqi Duan, Mengdi Wang, Martin J. Wainwright


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Boosting the Convergence of Reinforcement Learning-based Auto-pruning Using Historical Data


Jul 16, 2021
Jiandong Mu, Mengdi Wang, Feiwen Zhu, Jun Yang, Wei Lin, Wei Zhang


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On the Sample Complexity and Metastability of Heavy-tailed Policy Search in Continuous Control


Jun 15, 2021
Amrit Singh Bedi, Anjaly Parayil, Junyu Zhang, Mengdi Wang, Alec Koppel


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1$\times$N Block Pattern for Network Sparsity


Jun 15, 2021
Mingbao Lin, Yuchao Li, Yuxin Zhang, Bohong Chen, Fei Chao, Mengdi Wang, Shen Li, Jun Yang, Rongrong Ji


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You Only Compress Once: Towards Effective and Elastic BERT Compression via Exploit-Explore Stochastic Nature Gradient


Jun 04, 2021
Shaokun Zhang, Xiawu Zheng, Chenyi Yang, Yuchao Li, Yan Wang, Fei Chao, Mengdi Wang, Shen Li, Jun Yang, Rongrong Ji

* 12 pages, 3 figures 

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MARL with General Utilities via Decentralized Shadow Reward Actor-Critic


May 29, 2021
Junyu Zhang, Amrit Singh Bedi, Mengdi Wang, Alec Koppel


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Towards Compact CNNs via Collaborative Compression


May 24, 2021
Yuchao Li, Shaohui Lin, Jianzhuang Liu, Qixiang Ye, Mengdi Wang, Fei Chao, Fan Yang, Jincheng Ma, Qi Tian, Rongrong Ji

* This paper is published in CVPR 2021 

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Learning Good State and Action Representations via Tensor Decomposition


May 03, 2021
Chengzhuo Ni, Anru Zhang, Yaqi Duan, Mengdi Wang


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On the Convergence and Sample Efficiency of Variance-Reduced Policy Gradient Method


Feb 17, 2021
Junyu Zhang, Chengzhuo Ni, Zheng Yu, Csaba Szepesvari, Mengdi Wang


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Bootstrapping Statistical Inference for Off-Policy Evaluation


Feb 09, 2021
Botao Hao, Xiang Ji, Yaqi Duan, Hao Lu, Csaba Szepesvári, Mengdi Wang


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Bridging Exploration and General Function Approximation in Reinforcement Learning: Provably Efficient Kernel and Neural Value Iterations


Nov 09, 2020
Zhuoran Yang, Chi Jin, Zhaoran Wang, Mengdi Wang, Michael I. Jordan

* 76 pages. The short version of this work appears in NeurIPS 2020 

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High-Dimensional Sparse Linear Bandits


Nov 08, 2020
Botao Hao, Tor Lattimore, Mengdi Wang

* Accepted by NeurIPS 2020 

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Sparse Feature Selection Makes Batch Reinforcement Learning More Sample Efficient


Nov 08, 2020
Botao Hao, Yaqi Duan, Tor Lattimore, Csaba Szepesvári, Mengdi Wang


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Online Sparse Reinforcement Learning


Nov 08, 2020
Botao Hao, Tor Lattimore, Csaba Szepesvári, Mengdi Wang


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Generalized Leverage Score Sampling for Neural Networks


Sep 21, 2020
Jason D. Lee, Ruoqi Shen, Zhao Song, Mengdi Wang, Zheng Yu


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Variational Policy Gradient Method for Reinforcement Learning with General Utilities


Jul 04, 2020
Junyu Zhang, Alec Koppel, Amrit Singh Bedi, Csaba Szepesvari, Mengdi Wang


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Picasso: A Sparse Learning Library for High Dimensional Data Analysis in R and Python


Jun 27, 2020
Jason Ge, Xingguo Li, Haoming Jiang, Han Liu, Tong Zhang, Mengdi Wang, Tuo Zhao

* Journal of Machine Learning Research 20 (2019): 44-1 

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Model-Based Reinforcement Learning with Value-Targeted Regression


Jun 01, 2020
Alex Ayoub, Zeyu Jia, Csaba Szepesvari, Mengdi Wang, Lin F. Yang


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Cautious Reinforcement Learning via Distributional Risk in the Dual Domain


Feb 27, 2020
Junyu Zhang, Amrit Singh Bedi, Mengdi Wang, Alec Koppel


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Sketching Transformed Matrices with Applications to Natural Language Processing


Feb 23, 2020
Yingyu Liang, Zhao Song, Mengdi Wang, Lin F. Yang, Xin Yang

* AISTATS 2020 

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Minimax-Optimal Off-Policy Evaluation with Linear Function Approximation


Feb 21, 2020
Yaqi Duan, Mengdi Wang


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Unsupervised Common Question Generation from Multiple Documents using Reinforced Contrastive Coordinator


Nov 08, 2019
Woon Sang Cho, Yizhe Zhang, Sudha Rao, Asli Celikyilmaz, Chenyan Xiong, Jianfeng Gao, Mengdi Wang, Bill Dolan


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Continuous Control with Contexts, Provably


Oct 30, 2019
Simon S. Du, Ruosong Wang, Mengdi Wang, Lin F. Yang


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Characterizing Deep Learning Training Workloads on Alibaba-PAI


Oct 14, 2019
Mengdi Wang, Chen Meng, Guoping Long, Chuan Wu, Jun Yang, Wei Lin, Yangqing Jia

* Accepted by IISWC2019 

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Solving Discounted Stochastic Two-Player Games with Near-Optimal Time and Sample Complexity


Aug 29, 2019
Aaron Sidford, Mengdi Wang, Lin F. Yang, Yinyu Ye


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Voting-Based Multi-Agent Reinforcement Learning


Jul 02, 2019
Yue Xu, Zengde Deng, Mengdi Wang, Wenjun Xu, Anthony Man-Cho So, Shuguang Cui


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Learning Markov models via low-rank optimization


Jun 28, 2019
Ziwei Zhu, Xudong Li, Mengdi Wang, Anru Zhang

* 40 pages, 4 figures. arXiv admin note: text overlap with arXiv:1804.00795 

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Reinforcement Learning in Feature Space: Matrix Bandit, Kernels, and Regret Bound


Jun 13, 2019
Lin F. Yang, Mengdi Wang


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Feature-Based Q-Learning for Two-Player Stochastic Games


Jun 02, 2019
Zeyu Jia, Lin F. Yang, Mengdi Wang

* 23 pages 

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