Quanquan Gu

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Dongruo ZhouIndiana University BloomingtonVerified email at iu.edu
Jiawei HanAbel Bliss Professor of Computer Science, University of IllinoisVerified email at cs.uiuc.edu
Difan ZouThe University of Hong KongVerified email at cs.hku.hk
Yuan CaoThe University of Hong KongVerified email at hku.hk
Pan XuDuke UniversityVerified email at duke.edu
Jinghui ChenAssistant Professor of Information Sciences and Technology, Penn State UniversityVerified email at psu.edu
Weitong ZhangAssistant Professor, SDSS, UNC Chapel HillVerified email at unc.edu
Yizhou SunProfessor, Computer Science, UCLAVerified email at cs.ucla.edu
Vladimir BravermanVictor E. Cameron Professor of Computer Science, Rice UniversityVerified email at rice.edu
Tong ZhangUIUCVerified email at tongzhang-ml.org
Huizhuo YuanUniversity of California, Los AngelesVerified email at ucla.edu
Sham M KakadeHarvard UniversityVerified email at seas.harvard.edu
Jian MaRay and Stephanie Lane Professor of Computational Biology, Carnegie Mellon UniversityVerified email at cs.cmu.edu
Spencer FreiUC DavisVerified email at ucdavis.edu
Lihong Li (李力鸿)AmazonVerified email at amazon.com
Yuanzhi LiAssistant Professor at CMUVerified email at andrew.cmu.edu
Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC BerkeleyVerified email at cs.berkeley.edu
Mikhail (Misha) BelkinProfessor of Data Science, Halıcıoğlu Data Science Institute, CSE, UCSD, Amazon ScholarVerified email at ucsd.edu
Panagiotis D. ChristofidesWilliam D. Van Vorst Distinguished Professor and Department Chair of Chemical Engineering, UCLAVerified email at seas.ucla.edu
Huazheng WangAssistant Professor, Oregon State UniversityVerified email at oregonstate.edu

Quanquan Gu

Associate Professor of Computer Science, UCLA

Verified email at cs.ucla.edu - Homepage

Statistical Machine Learning Nonconvex Optimization Deep Learning Theory Reinforcement Learning AI for Science


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Active learning: A survey CC Aggarwal, X Kong, Q Gu, J Han, SY Philip Data classification, 599-634, 2014	3536*	2014
Generalized fisher score for feature selection Q Gu, Z Li, J Han Proceedings of the Twenty-Seventh Conference on Uncertainty in Artificial …, 2012	1063	2012
Personalized entity recommendation: A heterogeneous information network approach X Yu, X Ren, Y Sun, Q Gu, B Sturt, U Khandelwal, B Norick, J Han Proceedings of the 7th ACM international conference on Web search and data …, 2014	907	2014
Improving adversarial robustness requires revisiting misclassified examples Y Wang, D Zou, J Yi, J Bailey, X Ma, Q Gu International Conference on Learning Representations, 2020	798	2020
Gradient descent optimizes over-parameterized deep ReLU networks D Zou, Y Cao, D Zhou, Q Gu Machine Learning, 1-26, 2019	731	2019
Generalization bounds of stochastic gradient descent for wide and deep neural networks Y Cao, Q Gu Advances in neural information processing systems, 2019	425	2019
On the Convergence and Robustness of Adversarial Training Y Wang, X Ma, J Bailey, J Yi, B Zhou, Q Gu International Conference on Machine Learning 1, 2, 2019	420	2019
Layer-dependent importance sampling for training deep and large graph convolutional networks D Zou, Z Hu, Y Wang, S Jiang, Y Sun, Q Gu Advances in neural information processing systems, 2019	334	2019
Collaborative filtering: Weighted nonnegative matrix factorization incorporating user and item graphs Q Gu, J Zhou, C Ding Proceedings of the 2010 SIAM international conference on data mining, 199-210, 2010	315	2010
Co-clustering on manifolds Q Gu, J Zhou Proceedings of the 15th ACM SIGKDD international conference on Knowledge …, 2009	303	2009
Neural Contextual Bandits with Upper Confidence Bound-Based Exploration D Zhou, L Li, Q Gu International Conference on Machine Learning, 2020	264	2020
An improved analysis of training over-parameterized deep neural networks D Zou, Q Gu Advances in neural information processing systems, 2019	259	2019
Joint feature selection and subspace learning Q Gu, Z Li, J Han International Joint Conference on Artificial Intelligence 22 (1), 1294, 2011	256	2011
Neural Thompson Sampling W Zhang, D Zhou, L Li, Q Gu International Conference on Learning Representations, 2021	254	2021
Recommendation in heterogeneous information networks with implicit user feedback X Yu, X Ren, Y Sun, B Sturt, U Khandelwal, Q Gu, B Norick, J Han Proceedings of the 7th ACM conference on Recommender systems, 347-350, 2013	242	2013
Nearly Minimax Optimal Reinforcement Learning for Linear Mixture Markov Decision Processes D Zhou, Q Gu, C Szepesvari COLT, 2021	229	2021
Stochastic nested variance reduction for nonconvex optimization D Zhou, P Xu, Q Gu Advances in Neural Information Processing Systems, 3921-3932, 2018	225*	2018
Towards understanding the spectral bias of deep learning Y Cao, Z Fang, Y Wu, DX Zhou, Q Gu International Joint Conference on Artificial Intelligence, 2021	222	2021
Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States EY Cramer, EL Ray, VK Lopez, J Bracher, A Brennen, ... Proceedings of the National Academy of Sciences 119 (15), e2113561119, 2022	221	2022
Global convergence of Langevin dynamics based algorithms for nonconvex optimization P Xu, J Chen, D Zou, Q Gu Advances in Neural Information Processing Systems 31, 2018	221	2018

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