Quanquan Gu

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Jiawei HanAbel Bliss Professor of Computer Science, University of IllinoisVerified email at cs.uiuc.edu
Pan XuDuke UniversityVerified email at duke.edu
Jinghui ChenAssistant Professor of Information Sciences and Technology, Penn State UniversityVerified email at psu.edu
Yizhou SunAssociate Professor, Computer Science, UCLAVerified email at cs.ucla.edu
Jian MaRay and Stephanie Lane Professor of Computational Biology, Carnegie Mellon UniversityVerified email at cs.cmu.edu
Spencer FreiPostdoctoral Researcher, UC BerkeleyVerified email at berkeley.edu
Lihong Li (李力鸿)AmazonVerified email at amazon.com
Tong ZhangHKUSTVerified email at tongzhang-ml.org
Vladimir BravermanAssociate Professor of Computer Science, Johns Hopkins UniversityVerified email at cs.jhu.edu
Sham M KakadeHarvard UniversityVerified email at seas.harvard.edu
Csaba SzepesvariDeepMind & University of AlbertaVerified email at cs.ualberta.ca
Guido F. MontufarUCLA Departments of Mathematics and StatisticsVerified email at math.ucla.edu
Mikhail (Misha) BelkinProfessor of Data Science, Halıcıoğlu Data Science Institute, UCSDVerified email at ucsd.edu
Simon Shaolei DuAssistant Professor, School of Computer Science and Engineering, University of WashingtonVerified email at cs.washington.edu
Panagiotis D. ChristofidesWilliam D. Van Vorst Distinguished Professor and Department Chair of Chemical Engineering, UCLAVerified email at seas.ucla.edu
Philip LongGoogleVerified email at google.com
Rebecca WillettUniversity of Chicago, Professor of Statistics and Computer ScienceVerified email at uchicago.edu
Miryung KimFull Professor, Computer Science, University of California, Los AngelesVerified email at cs.ucla.edu
Zheng WenDeepMindVerified email at google.com
Amin KarbasiYale UniversityVerified email at yale.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


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	2613*	2014
Generalized fisher score for feature selection Q Gu, Z Li, J Han Proceedings of the Twenty-Seventh Conference on Uncertainty in Artificial …, 2012	765	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	619	2014
Gradient descent optimizes over-parameterized deep ReLU networks D Zou, Y Cao, D Zhou, Q Gu Machine Learning, 1-26, 2019	464	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	288	2010
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	268	2020
Co-clustering on manifolds Q Gu, J Zhou Proceedings of the 15th ACM SIGKDD international conference on Knowledge …, 2009	264	2009
Joint feature selection and subspace learning Q Gu, Z Li, J Han International Joint Conference on Artificial Intelligence 22 (1), 1294, 2011	223	2011
Generalization bounds of stochastic gradient descent for wide and deep neural networks Y Cao, Q Gu Advances in neural information processing systems, 2019	216	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	191	2019
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	169	2013
Learning a shared subspace for multi-task clustering and transductive transfer classification Q Gu, J Zhou 2009 Ninth IEEE International Conference on Data Mining, 159-168, 2009	167	2009
Stochastic nested variance reduction for nonconvex optimization D Zhou, P Xu, Q Gu Advances in Neural Information Processing Systems, 3921-3932, 2018	152*	2018
An improved analysis of training over-parameterized deep neural networks D Zou, Q Gu Advances in neural information processing systems, 2019	143	2019
Citation prediction in heterogeneous bibliographic networks X Yu, Q Gu, M Zhou, J Han Proceedings of the 2012 SIAM international conference on data mining, 1119-1130, 2012	142	2012
Cluscite: Effective citation recommendation by information network-based clustering X Ren, J Liu, X Yu, U Khandelwal, Q Gu, L Wang, J Han Proceedings of the 20th ACM SIGKDD international conference on Knowledge …, 2014	138	2014
Generalization error bounds of gradient descent for learning overparameterized deep relu networks Y Cao, Q Gu Proceedings of the AAAI Conference on Artificial Intelligence, 2020	135*	2020
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	135	2018
Clustered support vector machines Q Gu, J Han International Conference on Artificial Intelligence and Statistics, 307-315, 2013	131	2013
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 International Joint Conference on Artificial Intelligence, 2020	130	2020

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