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Faster Convergence of Stochastic Gradient Langevin Dynamics for Non-Log-Concave Sampling

Oct 19, 2020
Difan Zou, Pan Xu, Quanquan Gu

* 42 pages, 1 figure 

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Does Network Width Really Help Adversarial Robustness?

Oct 03, 2020
Boxi Wu, Jinghui Chen, Deng Cai, Xiaofei He, Quanquan Gu

* 19 pages, 4 tables, 4 figures 

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Efficient Robust Training via Backward Smoothing

Oct 03, 2020
Jinghui Chen, Yu Cheng, Zhe Gan, Quanquan Gu, Jingjing Liu

* 12 pages, 11 tables, 5 figures 

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Neural Thompson Sampling

Oct 02, 2020
Weitong Zhang, Dongruo Zhou, Lihong Li, Quanquan Gu

* 32 pages, 2 tables, 4 figures 

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Minimax Optimal Reinforcement Learning for Discounted MDPs

Oct 01, 2020
Jiafan He, Dongruo Zhou, Quanquan Gu

* 34 pages, 1 table 

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Agnostic Learning of Halfspaces with Gradient Descent via Soft Margins

Oct 01, 2020
Spencer Frei, Yuan Cao, Quanquan Gu

* 24 pages, 1 table 

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Provably Efficient Reinforcement Learning for Discounted MDPs with Feature Mapping

Jun 23, 2020
Dongruo Zhou, Jiafan He, Quanquan Gu

* 28 pages, 1 figure 

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RayS: A Ray Searching Method for Hard-label Adversarial Attack

Jun 23, 2020
Jinghui Chen, Quanquan Gu

* 9 pages, 4 figures, 9 tables. In KDD 2020 

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Revisiting Membership Inference Under Realistic Assumptions

Jun 21, 2020
Bargav Jayaraman, Lingxiao Wang, David Evans, Quanquan Gu


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Optimization Theory for ReLU Neural Networks Trained with Normalization Layers

Jun 11, 2020
Yonatan Dukler, Quanquan Gu, Guido Montúfar

* To be presented at ICML 2020 

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Agnostic Learning of a Single Neuron with Gradient Descent

Jun 11, 2020
Spencer Frei, Yuan Cao, Quanquan Gu

* 28 pages, 3 tables 

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A Finite Time Analysis of Two Time-Scale Actor Critic Methods

May 04, 2020
Yue Wu, Weitong Zhang, Pan Xu, Quanquan Gu

* 43 pages 

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Exploring Private Federated Learning with Laplacian Smoothing

May 01, 2020
Zhicong Liang, Bao Wang, Quanquan Gu, Stanley Osher, Yuan Yao


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MOTS: Minimax Optimal Thompson Sampling

Mar 03, 2020
Tianyuan Jin, Pan Xu, Jieming Shi, Xiaokui Xiao, Quanquan Gu

* 17 pages, 2 figures 

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On the Global Convergence of Training Deep Linear ResNets

Mar 02, 2020
Difan Zou, Philip M. Long, Quanquan Gu

* 26 pages, 1 figure. In ICLR 2020 

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Understanding the Intrinsic Robustness of Image Distributions using Conditional Generative Models

Mar 01, 2020
Xiao Zhang, Jinghui Chen, Quanquan Gu, David Evans

* 14 pages, 2 figures, 5 tables, AISTATS final paper reformatted for readability 

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Double Explore-then-Commit: Asymptotic Optimality and Beyond

Feb 21, 2020
Tianyuan Jin, Pan Xu, Xiaokui Xiao, Quanquan Gu

* 26 pages 

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Mean-Field Analysis of Two-Layer Neural Networks: Non-Asymptotic Rates and Generalization Bounds

Feb 10, 2020
Zixiang Chen, Yuan Cao, Quanquan Gu, Tong Zhang

* 50 pages, 1 table 

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A Finite-Time Analysis of Q-Learning with Neural Network Function Approximation

Dec 10, 2019
Pan Xu, Quanquan Gu

* 23 pages, 1 table. Under review by ICLR 2020 

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Rank Aggregation via Heterogeneous Thurstone Preference Models

Dec 03, 2019
Tao Jin, Pan Xu, Quanquan Gu, Farzad Farnoud

* 36 pages, 2 figures, 8 tables. In AAAI 2020 

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Towards Understanding the Spectral Bias of Deep Learning

Dec 03, 2019
Yuan Cao, Zhiying Fang, Yue Wu, Ding-Xuan Zhou, Quanquan Gu

* 26 pages, 4 figures 

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How Much Over-parameterization Is Sufficient to Learn Deep ReLU Networks?

Nov 27, 2019
Zixiang Chen, Yuan Cao, Difan Zou, Quanquan Gu

* 27 pages 

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Layer-Dependent Importance Sampling for Training Deep and Large Graph Convolutional Networks

Nov 17, 2019
Difan Zou, Ziniu Hu, Yewen Wang, Song Jiang, Yizhou Sun, Quanquan Gu

* Published in NeurIPS 2019 

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Tight Sample Complexity of Learning One-hidden-layer Convolutional Neural Networks

Nov 12, 2019
Yuan Cao, Quanquan Gu

* 45 pages, 3 figures, 1 table. In NeurIPS 2019 

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Neural Contextual Bandits with Upper Confidence Bound-Based Exploration

Nov 11, 2019
Dongruo Zhou, Lihong Li, Quanquan Gu

* 37 pages, 1 figure 

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Laplacian Smoothing Stochastic Gradient Markov Chain Monte Carlo

Nov 02, 2019
Bao Wang, Difan Zou, Quanquan Gu, Stanley Osher

* 27 pages, 5 figures 

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Efficient Privacy-Preserving Nonconvex Optimization

Oct 30, 2019
Lingxiao Wang, Bargav Jayaraman, David Evans, Quanquan Gu

* 26 pages, 3 figures, 5 tables 

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Algorithm-Dependent Generalization Bounds for Overparameterized Deep Residual Networks

Oct 07, 2019
Spencer Frei, Yuan Cao, Quanquan Gu

* 37 pages. In NeurIPS 2019 

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