| Active learning: A survey CC Aggarwal, X Kong, Q Gu, J Han, SY Philip Data Classification: Algorithms and Applications, 571-605, 2014 | 1886* | 2014 |
| Generalized fisher score for feature selection Q Gu, Z Li, J Han Proceedings of the Twenty-Seventh Conference on Uncertainty in Artificial …, 2012 | 499 | 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 | 371 | 2014 |
| 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 | 238 | 2010 |
| Co-clustering on manifolds Q Gu, J Zhou Proceedings of the 15th ACM SIGKDD international conference on Knowledge …, 2009 | 222 | 2009 |
| Gradient descent optimizes over-parameterized deep ReLU networks D Zou, Y Cao, D Zhou, Q Gu Machine Learning, 1-26, 2019 | 194 | 2019 |
| Joint feature selection and subspace learning Q Gu, Z Li, J Han International Joint Conference on Artificial Intelligence 22 (1), 1294, 2011 | 183 | 2011 |
| Learning the 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 | 148 | 2009 |
| 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 | 113 | 2012 |
| Clustered support vector machines Q Gu, J Han International Conference on Artificial Intelligence and Statistics, 307-315, 2013 | 112 | 2013 |
| 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 | 111 | 2013 |
| 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 | 98 | 2014 |
| Latent community topic analysis: Integration of community discovery with topic modeling Z Yin, L Cao, Q Gu, J Han ACM Transactions on Intelligent Systems and Technology (TIST) 3 (4), 1-21, 2012 | 95 | 2012 |
| Correlated multi-label feature selection Q Gu, Z Li, J Han Proceedings of the 20th ACM international conference on Information and …, 2011 | 84 | 2011 |
| High dimensional em algorithm: Statistical optimization and asymptotic normality Z Wang, Q Gu, Y Ning, H Liu Advances in neural information processing systems, 2521-2529, 2015 | 82* | 2015 |
| A network-assisted co-clustering algorithm to discover cancer subtypes based on gene expression Y Liu, Q Gu, JP Hou, J Han, J Ma BMC bioinformatics 15 (1), 1-11, 2014 | 76 | 2014 |
| Stochastic nested variance reduction for nonconvex optimization D Zhou, P Xu, Q Gu Advances in Neural Information Processing Systems, 3921-3932, 2018 | 73* | 2018 |
| Generalization error bounds of gradient descent for learning overparameterized deep relu networks Y Cao, Q Gu AAAI, 2020 | 70* | 2020 |
| Generalization bounds of stochastic gradient descent for wide and deep neural networks Y Cao, Q Gu Advances in Neural Information Processing Systems, 10836-10846, 2019 | 70 | 2019 |
| Linear discriminant dimensionality reduction Q Gu, Z Li, J Han Joint European conference on machine learning and knowledge discovery in …, 2011 | 67 | 2011 |
Jiawei HanAbel Bliss Professor of Computer Science, University of IllinoisVerified email at cs.uiuc.edu
