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Efficient Local Planning with Linear Function Approximation


Aug 12, 2021
Dong Yin, Botao Hao, Yasin Abbasi-Yadkori, Nevena Lazić, Csaba Szepesvári


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A Realistic Simulation Framework for Learning with Label Noise


Jul 23, 2021
Keren Gu, Xander Masotto, Vandana Bachani, Balaji Lakshminarayanan, Jack Nikodem, Dong Yin

* Datasets released at https://github.com/deepmind/deepmind-research/tree/master/noisy_label 

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Revisiting the Loss Weight Adjustment in Object Detection


Mar 18, 2021
Wenxin Yu, Bin Hu, Yucheng Hu, Tianxiang Lan, Yuanfan You, Dong Yin


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Improved Regret Bound and Experience Replay in Regularized Policy Iteration


Feb 25, 2021
Nevena Lazic, Dong Yin, Yasin Abbasi-Yadkori, Csaba Szepesvari


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The Effectiveness of Memory Replay in Large Scale Continual Learning


Oct 06, 2020
Yogesh Balaji, Mehrdad Farajtabar, Dong Yin, Alex Mott, Ang Li

* 15 pages 

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SOLA: Continual Learning with Second-Order Loss Approximation


Jun 19, 2020
Dong Yin, Mehrdad Farajtabar, Ang Li


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A maximum-entropy approach to off-policy evaluation in average-reward MDPs


Jun 17, 2020
Nevena Lazic, Dong Yin, Mehrdad Farajtabar, Nir Levine, Dilan Gorur, Chris Harris, Dale Schuurmans


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An Efficient Framework for Clustered Federated Learning


Jun 07, 2020
Avishek Ghosh, Jichan Chung, Dong Yin, Kannan Ramchandran

* 20 pages, 4 figures and 1 table 

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Mission Oriented Miniature Fixed-wing UAV Swarms: A Multi-layered and Distributed Architecture


Dec 13, 2019
Zhihong Liu, Xiangke Wang, Lincheng Shen, Shulong Zhao, Yirui Cong, Jie Li, Dong Yin, Shengde Jia, Xiaojia Xiang


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A Strong Feature Representation for Siamese Network Tracker


Jul 18, 2019
Zhipeng Zhou, Rui Zhang, Dong Yin


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Quantitative $W_1$ Convergence of Langevin-Like Stochastic Processes with Non-Convex Potential State-Dependent Noise


Jul 13, 2019
Xiang Cheng, Dong Yin, Peter L. Bartlett, Michael I. Jordan


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A Fourier Perspective on Model Robustness in Computer Vision


Jun 21, 2019
Dong Yin, Raphael Gontijo Lopes, Jonathon Shlens, Ekin D. Cubuk, Justin Gilmer


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Robust Federated Learning in a Heterogeneous Environment


Jun 16, 2019
Avishek Ghosh, Justin Hong, Dong Yin, Kannan Ramchandran

* 30 pages, 4 figures 

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Improving Robustness Without Sacrificing Accuracy with Patch Gaussian Augmentation


Jun 06, 2019
Raphael Gontijo Lopes, Dong Yin, Ben Poole, Justin Gilmer, Ekin D. Cubuk


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Rademacher Complexity for Adversarially Robust Generalization


Oct 29, 2018
Dong Yin, Kannan Ramchandran, Peter Bartlett


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Defending Against Saddle Point Attack in Byzantine-Robust Distributed Learning


Sep 14, 2018
Dong Yin, Yudong Chen, Kannan Ramchandran, Peter Bartlett


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Online Learning for Non-Stationary A/B Tests


May 27, 2018
Andrés Muñoz Medina, Sergei Vassilvitskii, Dong Yin


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A framework with updateable joint images re-ranking for Person Re-identification


Mar 08, 2018
Mingyue Yuan, Dong Yin, Jingwen Ding, Yuhao Luo, Zhipeng Zhou, Chengfeng Zhu, Rui Zhang

* 23 pages,5 figures. submitted to JVCI 

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Byzantine-Robust Distributed Learning: Towards Optimal Statistical Rates


Mar 05, 2018
Dong Yin, Yudong Chen, Kannan Ramchandran, Peter Bartlett


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Gradient Diversity: a Key Ingredient for Scalable Distributed Learning


Jan 07, 2018
Dong Yin, Ashwin Pananjady, Max Lam, Dimitris Papailiopoulos, Kannan Ramchandran, Peter Bartlett


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Distributed Sequence Memory of Multidimensional Inputs in Recurrent Networks


Jan 27, 2017
Adam Charles, Dong Yin, Christopher Rozell

* Journal of Machine Learning Research, 18:1-37 Jan. 2017 
* 37 pages, 3 figures 

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Sliding-Window Optimization on an Ambiguity-Clearness Graph for Multi-object Tracking


Nov 28, 2015
Qi Guo, Le Dan, Dong Yin, Xiangyang Ji


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