Dongruo Zhou

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Quanquan GuAssociate Professor of Computer Science, UCLAEmail yang diverifikasi di cs.ucla.edu
Jiafan HePhD student, Department of Computer Science, UCLAEmail yang diverifikasi di ucla.edu
Yuan CaoThe University of Hong KongEmail yang diverifikasi di hku.hk
Pan XuDuke UniversityEmail yang diverifikasi di duke.edu
Weitong ZhangAssistant Professor, SDSS, UNC Chapel HillEmail yang diverifikasi di unc.edu
Lihong Li (李力鸿)AmazonEmail yang diverifikasi di amazon.com
Jinghui ChenAssistant Professor of Information Sciences and Technology, Penn State UniversityEmail yang diverifikasi di psu.edu
Difan ZouThe University of Hong KongEmail yang diverifikasi di cs.hku.hk
Yiqi TangEmail yang diverifikasi di osu.edu
Zixiang ChenGraduate Student of CS, UCLAEmail yang diverifikasi di cs.ucla.edu
Csaba SzepesvariDeepMind & University of AlbertaEmail yang diverifikasi di cs.ualberta.ca
Ziyan YangRice UniversityEmail yang diverifikasi di rice.edu
Tianhao WangResearch Assistant Professor, Toyota Technological Institute at ChicagoEmail yang diverifikasi di ttic.edu
Jinfeng Yi (易津锋)Email yang diverifikasi di jd.com
Khashayar KhosraviQuantitative ResearcherEmail yang diverifikasi di stanford.edu
Vahab MirrokniGoogle Fellow, VP, Google ResearchEmail yang diverifikasi di google.com
Yue WuPostdoctoral Research Fellow, Princeton UniversityEmail yang diverifikasi di ucla.edu
Rebecca WillettUniversity of Chicago, Professor of Statistics and Computer ScienceEmail yang diverifikasi di uchicago.edu
Robert D NowakKeith and Jane Morgan Nosbusch Professor in ECE, Grace Wahba Professor of Data ScienceEmail yang diverifikasi di wisc.edu
Yinglun ZhuAssistant Professor of ECE/CSE at the University of California, RiversideEmail yang diverifikasi di ucr.edu

Ikuti

Dongruo Zhou

Indiana University Bloomington

Email yang diverifikasi di iu.edu - Beranda

Machine Learning


Judul Urutkan menurut kutipan Urutkan menurut tahun Urutkan menurut judul	Dikutip oleh Dikutip oleh	Tahun
Gradient descent optimizes over-parameterized deep ReLU networks D Zou, Y Cao, D Zhou, Q Gu Machine learning 109, 467-492, 2020	784	2020
Neural contextual bandits with UCB-based exploration D Zhou, L Li, Q Gu International Conference on Machine Learning, 11492-11502, 2020	294	2020
Neural thompson sampling W Zhang, D Zhou, L Li, Q Gu arXiv preprint arXiv:2010.00827, 2020	280	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	245	2021
Stochastic nested variance reduction for nonconvex optimization D Zhou, P Xu, Q Gu arXiv preprint arXiv:1806.07811, 2018	235*	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	218	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	212	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	109	2021
Stochastic variance-reduced cubic regularization methods D Zhou, P Xu, Q Gu Journal of Machine Learning Research 20 (134), 1-47, 2019	81*	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	74	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	65*	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	60	2023
Nearly minimax optimal reinforcement learning for discounted MDPs J He, D Zhou, Q Gu Advances in Neural Information Processing Systems 34, 2021	56*	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	52	2022
Lower bounds for smooth nonconvex finite-sum optimization D Zhou, Q Gu International Conference on Machine Learning, 7574-7583, 2019	52	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	51	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	44	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	41	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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