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Nan Jiang

Faculty of Information Technology, Beijing University of Technology, Beijing, China, Beijing Key Laboratory of Trusted Computing, Beijing, China, National Engineering Laboratory for Critical Technologies of Information Security Classified Protection, Beijing, China

Quantifying spatial homogeneity of urban road networks via graph neural networks

Jan 01, 2021
Jiawei Xue, Nan Jiang, Senwei Liang, Qiyuan Pang, Satish V. Ukkusuri, Jianzhu Ma

* 22 pages, 5 figures 

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Language Generation via Combinatorial Constraint Satisfaction: A Tree Search Enhanced Monte-Carlo Approach

Nov 30, 2020
Maosen Zhang, Nan Jiang, Lei Li, Yexiang Xue

* Findings of the Association for Computational Linguistics: EMNLP 2020, pages 1286-1298. November 16 - 20, 2020. 2020 Association for Computational Linguistics 
* Findings of the Association for Computational Linguistics: EMNLP 2020, pages 1286-1298. November 16 - 20, 2020. 2020 Association for Computational Linguistics 

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A Variant of the Wang-Foster-Kakade Lower Bound for the Discounted Setting

Nov 04, 2020
Philip Amortila, Nan Jiang, Tengyang Xie


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Improved Worst-Case Regret Bounds for Randomized Least-Squares Value Iteration

Oct 23, 2020
Priyank Agrawal, Jinglin Chen, Nan Jiang

* 36 pages 

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The 1st Tiny Object Detection Challenge:Methods and Results

Oct 06, 2020
Xuehui Yu, Zhenjun Han, Yuqi Gong, Nan Jiang, Jian Zhao, Qixiang Ye, Jie Chen, Yuan Feng, Bin Zhang, Xiaodi Wang, Ying Xin, Jingwei Liu, Mingyuan Mao, Sheng Xu, Baochang Zhang, Shumin Han, Cheng Gao, Wei Tang, Lizuo Jin, Mingbo Hong, Yuchao Yang, Shuiwang Li, Huan Luo, Qijun Zhao, Humphrey Shi

* ECCV2020 Workshop on Real-world Computer Vision from Inputs with Limited Quality (RLQ) and Tiny Object Detection Challenge 

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Batch Value-function Approximation with Only Realizability

Sep 17, 2020
Tengyang Xie, Nan Jiang


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A Question Type Driven and Copy Loss Enhanced Frameworkfor Answer-Agnostic Neural Question Generation

May 24, 2020
Xiuyu Wu, Nan Jiang, Yunfang Wu


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Q* Approximation Schemes for Batch Reinforcement Learning: A Theoretical Comparison

Apr 09, 2020
Tengyang Xie, Nan Jiang


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$Q^\star$ Approximation Schemes for Batch Reinforcement Learning: A Theoretical Comparison

Mar 11, 2020
Tengyang Xie, Nan Jiang


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Minimax Confidence Interval for Off-Policy Evaluation and Policy Optimization

Feb 26, 2020
Nan Jiang, Jiawei Huang


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RL-Duet: Online Music Accompaniment Generation Using Deep Reinforcement Learning

Feb 08, 2020
Nan Jiang, Sheng Jin, Zhiyao Duan, Changshui Zhang


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Scale Match for Tiny Person Detection

Dec 23, 2019
Xuehui Yu, Yuqi Gong, Nan Jiang, Qixiang Ye, Zhenjun Han

* accepted by WACV2020 

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Empirical Study of Off-Policy Policy Evaluation for Reinforcement Learning

Nov 15, 2019
Cameron Voloshin, Hoang M. Le, Nan Jiang, Yisong Yue

* Main paper is 8 pages. The appendix contains many pages of tables 

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Minimax Weight and Q-Function Learning for Off-Policy Evaluation

Nov 02, 2019
Masatoshi Uehara, Nan Jiang


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Sample Complexity of Reinforcement Learning using Linearly Combined Model Ensembles

Oct 23, 2019
Aditya Modi, Nan Jiang, Ambuj Tewari, Satinder Singh


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From Importance Sampling to Doubly Robust Policy Gradient

Oct 20, 2019
Jiawei Huang, Nan Jiang

* 30 pages; 1 figure 

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On Value Functions and the Agent-Environment Boundary

May 30, 2019
Nan Jiang

* 16 pages 

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Provably Efficient Q-Learning with Low Switching Cost

May 30, 2019
Yu Bai, Tengyang Xie, Nan Jiang, Yu-Xiang Wang


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Information-Theoretic Considerations in Batch Reinforcement Learning

May 01, 2019
Jinglin Chen, Nan Jiang

* Published in ICML 2019 

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Provably efficient RL with Rich Observations via Latent State Decoding

Jan 25, 2019
Simon S. Du, Akshay Krishnamurthy, Nan Jiang, Alekh Agarwal, Miroslav Dudík, John Langford


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Model-Based Reinforcement Learning in Contextual Decision Processes

Nov 21, 2018
Wen Sun, Nan Jiang, Akshay Krishnamurthy, Alekh Agarwal, John Langford

* 30 

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On Oracle-Efficient PAC RL with Rich Observations

Oct 31, 2018
Christoph Dann, Nan Jiang, Akshay Krishnamurthy, Alekh Agarwal, John Langford, Robert E. Schapire

* appearing at NIPS 18; full paper including appendix 

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Why Do Neural Response Generation Models Prefer Universal Replies?

Aug 28, 2018
Bowen Wu, Nan Jiang, Zhifeng Gao, Suke Li, Wenge Rong, Baoxun Wang


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Hierarchical Imitation and Reinforcement Learning

Jun 09, 2018
Hoang M. Le, Nan Jiang, Alekh Agarwal, Miroslav Dudík, Yisong Yue, Hal Daumé III

* Proceedings of the 35th International Conference on Machine Learning (ICML 2018) 

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Image Classification Based on Quantum KNN Algorithm

May 16, 2018
Yijie Dang, Nan Jiang, Hao Hu, Zhuoxiao Ji, Wenyin Zhang

* 19 pages, 9 Postscript figures 

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Optimizing Recurrent Neural Networks Architectures under Time Constraints

Feb 21, 2018
Junqi Jin, Ziang Yan, Kun Fu, Nan Jiang, Changshui Zhang

* Withdrawn due to incompleteness and some overlaps with existing literatures, I will resubmit adding further results 

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