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Quanquan Gu
Quanquan Gu
Associate Professor (Effective July, 2022) of Computer Science, UCLA
Verified email at cs.ucla.edu - Homepage
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
2572*2014
Generalized fisher score for feature selection
Q Gu, Z Li, J Han
Proceedings of the Twenty-Seventh Conference on Uncertainty in Artificial …, 2012
7422012
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
5982014
Gradient descent optimizes over-parameterized deep ReLU networks
D Zou, Y Cao, D Zhou, Q Gu
Machine Learning, 1-26, 2019
4552019
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
2862010
Co-clustering on manifolds
Q Gu, J Zhou
Proceedings of the 15th ACM SIGKDD international conference on Knowledge …, 2009
2622009
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
2462020
Joint feature selection and subspace learning
Q Gu, Z Li, J Han
International Joint Conference on Artificial Intelligence 22 (1), 1294, 2011
2202011
Generalization bounds of stochastic gradient descent for wide and deep neural networks
Y Cao, Q Gu
Advances in neural information processing systems, 2019
2082019
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
1842019
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
1662009
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
1632013
Stochastic nested variance reduction for nonconvex optimization
D Zhou, P Xu, Q Gu
Advances in Neural Information Processing Systems, 3921-3932, 2018
149*2018
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
1402012
An improved analysis of training over-parameterized deep neural networks
D Zou, Q Gu
Advances in neural information processing systems, 2019
1392019
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
1352014
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
1312018
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
130*2020
Clustered support vector machines
Q Gu, J Han
International Conference on Artificial Intelligence and Statistics, 307-315, 2013
1292013
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
1222020
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