Xinhua Zhang

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Dale SchuurmansResearch Scientist, Google Brain / Professor, University of AlbertaVerified 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
Hao ChengMicrosoft ResearchVerified email at microsoft.com
Martha WhiteUniversity of AlbertaVerified email at ualberta.ca
Zhan Shiuniversity of illinois at chicagoVerified email at uic.edu
Mohammad Ali BashiriUniversity of Illinois at ChicagoVerified email at uic.edu
Arthur GrettonGatsby Computational Neuroscience Unit, UCLVerified email at gatsby.ucl.ac.uk
Alex SmolaAmazon Web ServicesVerified email at smola.org
Le SongBiomap, Mohamed bin Zayed University of Artificial IntelligenceVerified email at biomap.com
Brian D ZiebartAssociate Professor of Computer Science, University of Illinois at ChicagoVerified email at uic.edu
Hongwei JinArgonne National LaboratoryVerified email at anl.gov
Wee Sun LeeProfessor, Department of Computer Science, National University of SingaporeVerified email at comp.nus.edu.sg
Vignesh GanapathiramanUniversity of Illinois at ChicagoVerified email at uic.edu
Shin MatsushimaThe University of TokyoVerified email at ds.itc.u-tokyo.ac.jp
Hyokun YunMachine Learning Scientist at AmazonVerified email at amazon.com
Rizal FathonyCarnegie Mellon UniversityVerified email at cs.cmu.edu
Özlem AslanResearch Scientist at DeepMindVerified email at google.com
Yingyi MaMeta AIVerified email at fb.com

Xinhua Zhang

University of Illinois at 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	162	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	107	2012
Support Vector Machines X Zhang Encyclopedia of Machine Learning, 941-946, 2011	73*	2011
Hyperparameter learning for graph based semi-supervised learning algorithms X Zhang, WS Lee Advances in neural information processing systems, 1585-1592, 2006	69	2006
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	66	2008
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	46	2010
Generalized conditional gradient for sparse estimation Y Yu, X Zhang, D Schuurmans Journal of Machine Learning Research 18 (144), 1-46, 2017	45	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	41	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	40	2008
Convex Sparse Coding, Subspace Learning, and Semi-Supervised Extensions. X Zhang, Y Yu, M White, R Huang, D Schuurmans AAAI, 2011	37	2011
Convex deep learning via normalized kernels Ö Aslan, X Zhang, D Schuurmans Advances in Neural Information Processing Systems, 3275-3283, 2014	33	2014
Latent adversarial training of graph convolution networks H Jin, X Zhang ICML Workshop on Learning and Reasoning with Graph-Structured Representations, 2019	32	2019
New approximation algorithms for minimum enclosing convex shapes A Saha, SVN Vishwanathan, X Zhang Proceedings of the twenty-second annual ACM-SIAM symposium on Discrete …, 2011	29	2011
Smoothing multivariate performance measures X Zhang, A Saha, SVN Vishwanathan Journal of Machine Learning Research 13 (Dec), 3623-3680, 2012	28	2012
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	28	2007
Decomposition-Invariant Conditional Gradient for General Polytopes with Line Search MA Bashiri, X Zhang Advances in Neural Information Processing Systems, 2687-2697, 2017	27	2017
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	27	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	27	2016
Convex two-layer modeling Ö Aslan, H Cheng, X Zhang, D Schuurmans Advances in Neural Information Processing Systems 26, 2985-2993, 2013	26	2013
New approximation algorithms for minimum enclosing convex shapes A Saha, SVN Vishwanathan, X Zhang Proceedings of the twenty-second annual ACM-SIAM symposium on Discrete …, 2011	26	2011

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