Quanquan Gu

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Referințe bibliografice	23569	17952
h-index	71	64
i10-index	223	203

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Dongruo ZhouIndiana University BloomingtonAdresă de e-mail confirmată pe iu.edu
Jiawei HanAbel Bliss Professor of Computer Science, University of IllinoisAdresă de e-mail confirmată pe cs.uiuc.edu
Difan ZouThe University of Hong KongAdresă de e-mail confirmată pe cs.hku.hk
Yuan CaoThe University of Hong KongAdresă de e-mail confirmată pe hku.hk
Pan XuDuke UniversityAdresă de e-mail confirmată pe duke.edu
Jinghui ChenAssistant Professor of Information Sciences and Technology, Penn State UniversityAdresă de e-mail confirmată pe psu.edu
Weitong ZhangAssistant Professor, SDSS, UNC Chapel HillAdresă de e-mail confirmată pe unc.edu
Huizhuo YuanUniversity of California, Los AngelesAdresă de e-mail confirmată pe ucla.edu
Yizhou SunProfessor, Computer Science, UCLAAdresă de e-mail confirmată pe cs.ucla.edu
Tong ZhangUIUCAdresă de e-mail confirmată pe tongzhang-ml.org
Vladimir BravermanProfessor of Computer Science, Johns Hopkins University; Google Research; Adjunct Professor, Rice U.Adresă de e-mail confirmată pe cs.jhu.edu
Sham M KakadeHarvard UniversityAdresă de e-mail confirmată pe seas.harvard.edu
Jian MaRay and Stephanie Lane Professor of Computational Biology, Carnegie Mellon UniversityAdresă de e-mail confirmată pe cs.cmu.edu
Spencer FreiGoogle DeepMindAdresă de e-mail confirmată pe google.com
Yuanzhi LiAssistant Professor at CMUAdresă de e-mail confirmată pe andrew.cmu.edu
Lihong Li (李力鸿)AmazonAdresă de e-mail confirmată pe amazon.com
Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC BerkeleyAdresă de e-mail confirmată pe cs.berkeley.edu
Chenlu YeComputer Science, University of Illinois Urbana-ChampaignAdresă de e-mail confirmată pe illinois.edu
Mikhail (Misha) BelkinProfessor of Data Science, Halıcıoğlu Data Science Institute, CSE, UCSD, Amazon ScholarAdresă de e-mail confirmată pe ucsd.edu
Panagiotis D. ChristofidesWilliam D. Van Vorst Distinguished Professor and Department Chair of Chemical Engineering, UCLAAdresă de e-mail confirmată pe seas.ucla.edu

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Quanquan Gu

Associate Professor of Computer Science, UCLA

Adresă de e-mail confirmată pe cs.ucla.edu - Pagina de pornire

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


Titlu Sortați după descrierea bibliografică Sortați după an Sortați după titlu	Citat de Citat de	Anul
Active learning: A survey CC Aggarwal, X Kong, Q Gu, J Han, SY Philip Data classification, 599-634, 2014	3688*	2014
Generalized fisher score for feature selection Q Gu, Z Li, J Han Proceedings of the Twenty-Seventh Conference on Uncertainty in Artificial …, 2012	1093	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	934	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	866	2020
Gradient descent optimizes over-parameterized deep ReLU networks D Zou, Y Cao, D Zhou, Q Gu Machine Learning, 1-26, 2019	770	2019
Self-play fine-tuning converts weak language models to strong language models Z Chen, Y Deng, H Yuan, K Ji, Q Gu arXiv preprint arXiv:2401.01335, 2024	460	2024
Generalization bounds of stochastic gradient descent for wide and deep neural networks Y Cao, Q Gu Advances in neural information processing systems, 2019	451	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	438	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	368	2019
Position: TrustLLM: Trustworthiness in large language models Y Huang, L Sun, H Wang, S Wu, Q Zhang, Y Li, C Gao, Y Huang, W Lyu, ... International Conference on Machine Learning, 20166-20270, 2024	319*	2024
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	316	2010
Neural Contextual Bandits with Upper Confidence Bound-Based Exploration D Zhou, L Li, Q Gu International Conference on Machine Learning, 2020	306	2020
Co-clustering on manifolds Q Gu, J Zhou Proceedings of the 15th ACM SIGKDD international conference on Knowledge …, 2009	304	2009
An improved analysis of training over-parameterized deep neural networks D Zou, Q Gu Advances in neural information processing systems, 2019	285	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
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	255	2022
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	250	2021
Nearly Minimax Optimal Reinforcement Learning for Linear Mixture Markov Decision Processes D Zhou, Q Gu, C Szepesvari COLT, 2021	247	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	244	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	238	2020

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