Dongruo Zhou

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	Total	Desde 2019
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Quanquan GuAssociate Professor of Computer Science, UCLADirección de correo verificada de cs.ucla.edu
Jiafan HePhD student, Department of Computer Science, UCLADirección de correo verificada de ucla.edu
Yuan CaoThe University of Hong KongDirección de correo verificada de hku.hk
Pan XuDuke UniversityDirección de correo verificada de duke.edu
Weitong ZhangAssistant Professor, SDSS, UNC Chapel HillDirección de correo verificada de unc.edu
Lihong Li (李力鸿)AmazonDirección de correo verificada de amazon.com
Jinghui ChenAssistant Professor of Information Sciences and Technology, Penn State UniversityDirección de correo verificada de psu.edu
Difan ZouThe University of Hong KongDirección de correo verificada de cs.hku.hk
Yiqi TangDirección de correo verificada de osu.edu
Zixiang ChenGraduate Student of CS, UCLADirección de correo verificada de cs.ucla.edu
Csaba SzepesvariDeepMind & University of AlbertaDirección de correo verificada de cs.ualberta.ca
Ziyan YangRice UniversityDirección de correo verificada de rice.edu
Tianhao WangResearch Assistant Professor, Toyota Technological Institute at ChicagoDirección de correo verificada de ttic.edu
Jinfeng Yi (易津锋)Dirección de correo verificada de jd.com
Yue WuPostdoctoral Research Fellow, Princeton UniversityDirección de correo verificada de ucla.edu
Khashayar KhosraviQuantitative ResearcherDirección de correo verificada de stanford.edu
Vahab MirrokniGoogle Fellow, VP, Google ResearchDirección de correo verificada de google.com
Rebecca WillettUniversity of Chicago, Professor of Statistics and Computer ScienceDirección de correo verificada de uchicago.edu
Robert D NowakKeith and Jane Morgan Nosbusch Professor in ECE, Grace Wahba Professor of Data ScienceDirección de correo verificada de wisc.edu
Yinglun ZhuAssistant Professor of ECE/CSE at the University of California, RiversideDirección de correo verificada de ucr.edu

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Dongruo Zhou

Indiana University Bloomington

Dirección de correo verificada de iu.edu - Página principal

Machine Learning


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
Gradient descent optimizes over-parameterized deep ReLU networks D Zou, Y Cao, D Zhou, Q Gu Machine learning 109, 467-492, 2020	764	2020
Neural contextual bandits with UCB-based exploration D Zhou, L Li, Q Gu International Conference on Machine Learning, 11492-11502, 2020	277	2020
Neural thompson sampling W Zhang, D Zhou, L Li, Q Gu arXiv preprint arXiv:2010.00827, 2020	263	2020
Nearly minimax optimal reinforcement learning for linear mixture markov decision processes D Zhou, Q Gu, C Szepesvari Conference on Learning Theory, 4532-4576, 2021	238	2021
Stochastic nested variance reduction for nonconvex optimization D Zhou, P Xu, Q Gu arXiv preprint arXiv:1806.07811, 2018	231*	2018
Closing the generalization gap of adaptive gradient methods in training deep neural networks J Chen, D Zhou, Y Tang, Z Yang, Y Cao, Q Gu arXiv preprint arXiv:1806.06763, 2018	210	2018
On the convergence of adaptive gradient methods for nonconvex optimization D Zhou, J Chen, Y Cao, Z Yang, Q Gu arXiv preprint arXiv:1808.05671, 2018	207	2018
Provably efficient reinforcement learning for discounted mdps with feature mapping D Zhou, J He, Q Gu International Conference on Machine Learning, 12793-12802, 2021	148	2021
Logarithmic regret for reinforcement learning with linear function approximation J He, D Zhou, Q Gu International Conference on Machine Learning, 4171-4180, 2021	108	2021
Stochastic variance-reduced cubic regularization methods D Zhou, P Xu, Q Gu Journal of Machine Learning Research 20 (134), 1-47, 2019	76*	2019
A frank-wolfe framework for efficient and effective adversarial attacks J Chen, D Zhou, J Yi, Q Gu Proceedings of the AAAI conference on artificial intelligence 34 (04), 3486-3494, 2020	68	2020
Almost optimal algorithms for two-player zero-sum linear mixture markov games Z Chen, D Zhou, Q Gu International Conference on Algorithmic Learning Theory, 227-261, 2022	63*	2022
Nearly minimax optimal reinforcement learning for linear markov decision processes J He, H Zhao, D Zhou, Q Gu International Conference on Machine Learning, 12790-12822, 2023	57	2023
Nearly minimax optimal reinforcement learning for discounted MDPs J He, D Zhou, Q Gu Advances in Neural Information Processing Systems 34, 2021	54*	2021
Nearly optimal algorithms for linear contextual bandits with adversarial corruptions J He, D Zhou, T Zhang, Q Gu Advances in neural information processing systems 35, 34614-34625, 2022	51	2022
Lower bounds for smooth nonconvex finite-sum optimization D Zhou, Q Gu International Conference on Machine Learning, 7574-7583, 2019	50	2019
Provably efficient reinforcement learning with linear function approximation under adaptivity constraints T Wang, D Zhou, Q Gu Advances in Neural Information Processing Systems 34, 13524-13536, 2021	49	2021
Computationally efficient horizon-free reinforcement learning for linear mixture mdps D Zhou, Q Gu Advances in neural information processing systems 35, 36337-36349, 2022	43	2022
Variance-aware off-policy evaluation with linear function approximation Y Min, T Wang, D Zhou, Q Gu Advances in neural information processing systems 34, 7598-7610, 2021	39	2021
Reward-free model-based reinforcement learning with linear function approximation W Zhang, D Zhou, Q Gu Advances in Neural Information Processing Systems 34, 1582-1593, 2021	37	2021

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