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Online Bootstrap Inference For Policy Evaluation in Reinforcement Learning


Aug 08, 2021
Pratik Ramprasad, Yuantong Li, Zhuoran Yang, Zhaoran Wang, Will Wei Sun, Guang Cheng


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Optimum-statistical collaboration towards efficient black-box optimization


Jun 17, 2021
Wenjie Li, Chihua Wang, Guang Cheng


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Distributed Bootstrap for Simultaneous Inference Under High Dimensionality


Feb 19, 2021
Yang Yu, Shih-Kang Chao, Guang Cheng

* arXiv admin note: text overlap with arXiv:2002.08443 

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Variance Reduction on Adaptive Stochastic Mirror Descent


Dec 26, 2020
Wenjie Li, Zhanyu Wang, Yichen Zhang, Guang Cheng

* NeurIPS 2020 OPT workshop 

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Union-net: A deep neural network model adapted to small data sets


Dec 24, 2020
Qingfang He, Guang Cheng, Zhiying Lin

* 13 pages, 6 figures 

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Adversarially Robust Estimate and Risk Analysis in Linear Regression


Dec 18, 2020
Yue Xing, Ruizhi Zhang, Guang Cheng


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Online Forgetting Process for Linear Regression Models


Dec 03, 2020
Yuantong Li, Chi-hua Wang, Guang Cheng


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Efficient Variational Inference for Sparse Deep Learning with Theoretical Guarantee


Nov 15, 2020
Jincheng Bai, Qifan Song, Guang Cheng

* Accepted to NeurIPS 2020 

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Nearly Optimal Variational Inference for High Dimensional Regression with Shrinkage Priors


Oct 24, 2020
Jincheng Bai, Qifan Song, Guang Cheng


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On the Generalization Properties of Adversarial Training


Aug 15, 2020
Yue Xing, Qifan Song, Guang Cheng


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Regularization Matters: A Nonparametric Perspective on Overparametrized Neural Network


Jul 06, 2020
Wenjia Wang, Tianyang Hu, Cong Lin, Guang Cheng


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Online Regularization for High-Dimensional Dynamic Pricing Algorithms


Jul 05, 2020
Chi-Hua Wang, Zhanyu Wang, Will Wei Sun, Guang Cheng


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Directional Pruning of Deep Neural Networks


Jun 16, 2020
Shih-Kang Chao, Zhanyu Wang, Yue Xing, Guang Cheng

* 29 pages 

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On Deep Instrumental Variables Estimate


Apr 30, 2020
Ruiqi Liu, Zuofeng Shang, Guang Cheng


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Online Batch Decision-Making with High-Dimensional Covariates


Feb 27, 2020
Chi-Hua Wang, Guang Cheng


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Simultaneous Inference for Massive Data: Distributed Bootstrap


Feb 19, 2020
Yang Yu, Shih-Kang Chao, Guang Cheng


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Residual Bootstrap Exploration for Bandit Algorithms


Feb 19, 2020
Chi-Hua Wang, Yang Yu, Botao Hao, Guang Cheng

* The first two authors contributed equally 

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Predictive Power of Nearest Neighbors Algorithm under Random Perturbation


Feb 13, 2020
Yue Xing, Qifan Song, Guang Cheng


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Sharp Rate of Convergence for Deep Neural Network Classifiers under the Teacher-Student Setting


Feb 01, 2020
Tianyang Hu, Zuofeng Shang, Guang Cheng


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Optimal Rate of Convergence for Deep Neural Network Classifiers under the Teacher-Student Setting


Jan 19, 2020
Tianyang Hu, Zuofeng Shang, Guang Cheng


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Benefit of Interpolation in Nearest Neighbor Algorithms


Sep 25, 2019
Yue Xing, Qifan Song, Guang Cheng

* Under review as a conference paper at ICLR 2020 

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A generalization of regularized dual averaging and its dynamics


Sep 22, 2019
Shih-Kang Chao, Guang Cheng


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Machine Learning in/for Blockchain: Future and Challenges


Sep 12, 2019
Fang Chen, Hong Wan, Hua Cai, Guang Cheng

* A preliminary version to be improved soon 

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Rates of Convergence for Large-scale Nearest Neighbor Classification


Sep 03, 2019
Xingye Qiao, Jiexin Duan, Guang Cheng

* A camera ready version will appear in NeurIPS 2019 

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Bootstrapping Upper Confidence Bound


Jul 23, 2019
Botao Hao, Yasin Abbasi-Yadkori, Zheng Wen, Guang Cheng


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An Efficient Network Intrusion Detection System Based on Feature Selection and Ensemble Classifier


Apr 02, 2019
Yu-Yang Zhou, Guang Cheng


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Stein Neural Sampler


Oct 08, 2018
Tianyang Hu, Zixiang Chen, Hanxi Sun, Jincheng Bai, Mao Ye, Guang Cheng


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Early Stopping for Nonparametric Testing


Sep 17, 2018
Meimei Liu, Guang Cheng

* To appear in NIPS 2018 

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