Xinhua Zhang

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Dale SchuurmansUniversity of Alberta, Google DeepMindVerified email at cs.ualberta.ca
Yaoliang YuUniversity of WaterlooVerified email at uwaterloo.ca
S V N VishwanathanAssociate Professor of Statistics and Computer Science, Purdue UniversityVerified email at stat.purdue.edu
Ankan SahaSenior Staff Applied Researcher, LinkedinVerified email at linkedin.com
Hongwei JinArgonne National LaboratoryVerified email at anl.gov
Zhan Shiuniversity of illinois at chicagoVerified email at uic.edu
Brian D ZiebartProfessor of Computer Science, University of Illinois at ChicagoVerified email at uic.edu
Martha WhiteUniversity of AlbertaVerified email at ualberta.ca
Mohammad Ali BashiriMicrosoftVerified email at microsoft.com
Hao ChengMicrosoft ResearchVerified email at microsoft.com
Arthur GrettonGatsby Computational Neuroscience Unit and Google DeepmindVerified email at gatsby.ucl.ac.uk
Alex SmolaBoson AIVerified email at smola.org
Le SongBiomap, Mohamed bin Zayed University of Artificial IntelligenceVerified email at biomap.com
Rizal FathonyApplied Reseacher | AI Foundations @ Capital OneVerified email at capitalone.com
Yingyi MaResearch ScientistVerified email at meta.com
Wee Sun LeeProfessor, Department of Computer Science, National University of SingaporeVerified email at comp.nus.edu.sg
Vignesh GanapathiramanYahoo! ResearchVerified email at yahooinc.com
Shin MatsushimaThe University of TokyoVerified email at ds.itc.u-tokyo.ac.jp
Hyokun YunMachine Learning Scientist at AmazonVerified email at amazon.com
Zishun YuPhD student, University of Illinois ChicagoVerified email at uic.edu

Xinhua Zhang

University of Illinois Chicago

Verified email at uic.edu - Homepage

Machine Learning


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Convex multi-view subspace learning M White, Y Yu, X Zhang, D Schuurmans Advances in Neural Information Processing Systems, 1673-1681, 2012	201	2012
Accelerated training for matrix-norm regularization: A boosting approach X Zhang, Y Yu, D Schuurmans Advances in Neural Information Processing Systems, 2906-2914, 2012	111	2012
Support Vector Machines X Zhang Encyclopedia of Machine Learning, 941-946, 2011	93*	2011
Tailoring density estimation via reproducing kernel moment matching L Song, X Zhang, A Smola, A Gretton, B Schölkopf Proceedings of the 25th international conference on Machine learning, 992-999, 2008	81	2008
Hyperparameter learning for graph based semi-supervised learning algorithms X Zhang, WS Lee Advances in neural information processing systems, 1585-1592, 2006	76	2006
Latent adversarial training of graph convolution networks H Jin, X Zhang ICML Workshop on Learning and Reasoning with Graph-Structured Representations, 2019	59	2019
Bayesian online learning for multi-label and multi-variate performance measures X Zhang, T Graepel, R Herbrich Proceedings of the Thirteenth International Conference on Artificial …, 2010	52	2010
Certified Robustness of Graph Convolution Networks for Graph Classification under Topological Attacks H Jin, Z Shi, VJSA Peruri, X Zhang Advances in Neural Information Processing Systems 33, 2020	50	2020
Generalized conditional gradient for sparse estimation Y Yu, X Zhang, D Schuurmans Journal of Machine Learning Research 18 (144), 1-46, 2017	50	2017
Kernel measures of independence for non-iid data X Zhang, L Song, A Gretton, A Smola Advances in neural information processing systems 21, 1937-1944, 2008	45	2008
Consistent image analogies using semi-supervised learning L Cheng, SVN Vishwanathan, X Zhang 2008 IEEE Conference on Computer Vision and Pattern Recognition, 1-8, 2008	43	2008
Smoothing multivariate performance measures X Zhang, A Saha, SVN Vishwanathan Journal of Machine Learning Research 13 (Dec), 3623-3680, 2012	39	2012
Convex Sparse Coding, Subspace Learning, and Semi-Supervised Extensions. X Zhang, Y Yu, M White, R Huang, D Schuurmans AAAI, 2011	39	2011
Convex deep learning via normalized kernels Ö Aslan, X Zhang, D Schuurmans Advances in Neural Information Processing Systems, 3275-3283, 2014	36	2014
Conditional random fields for multi-agent reinforcement learning X Zhang, D Aberdeen, SVN Vishwanathan Proceedings of the 24th international conference on Machine learning, 1143-1150, 2007	32	2007
Decomposition-Invariant Conditional Gradient for General Polytopes with Line Search MA Bashiri, X Zhang Advances in Neural Information Processing Systems, 2687-2697, 2017	30	2017
Scalable and Sound Low-Rank Tensor Learning H Cheng, Y Yu, X Zhang, E Xing, D Schuurmans Proceedings of the 19th International Conference on Artificial Intelligence …, 2016	30	2016
Pseudo-MDPs and factored linear action models H Yao, C Szepesvári, BA Pires, X Zhang 2014 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement …, 2014	30	2014
Generalised lipschitz regularisation equals distributional robustness Z Cranko, Z Shi, X Zhang, R Nock, S Kornblith International Conference on Machine Learning, 2178-2188, 2021	28	2021
Bregman Divergence for Stochastic Variance Reduction: Saddle-Point and Adversarial Prediction Z Shi, X Zhang, Y Yu Advances in Neural Information Processing Systems, 6033-6043, 2017	28	2017

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