Xinhua Zhang

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Dale SchuurmansUniversity of Alberta, Google DeepMindDirección de correo verificada de cs.ualberta.ca
Yaoliang YuUniversity of WaterlooDirección de correo verificada de uwaterloo.ca
S V N VishwanathanAssociate Professor of Statistics and Computer Science, Purdue UniversityDirección de correo verificada de stat.purdue.edu
Ankan SahaSenior Staff Applied Researcher, LinkedinDirección de correo verificada de linkedin.com
Hongwei JinArgonne National LaboratoryDirección de correo verificada de anl.gov
Zhan Shiuniversity of illinois at chicagoDirección de correo verificada de uic.edu
Brian D ZiebartProfessor of Computer Science, University of Illinois at ChicagoDirección de correo verificada de uic.edu
Martha WhiteUniversity of AlbertaDirección de correo verificada de ualberta.ca
Mohammad Ali BashiriMicrosoftDirección de correo verificada de microsoft.com
Hao ChengMicrosoft ResearchDirección de correo verificada de microsoft.com
Arthur GrettonGatsby Computational Neuroscience Unit and Google DeepmindDirección de correo verificada de gatsby.ucl.ac.uk
Alex SmolaBoson AIDirección de correo verificada de smola.org
Le SongBiomap, Mohamed bin Zayed University of Artificial IntelligenceDirección de correo verificada de biomap.com
Rizal FathonyApplied Reseacher | AI Foundations @ Capital OneDirección de correo verificada de capitalone.com
Yingyi MaResearch ScientistDirección de correo verificada de meta.com
Wee Sun LeeProfessor, Department of Computer Science, National University of SingaporeDirección de correo verificada de comp.nus.edu.sg
Vignesh GanapathiramanYahoo! ResearchDirección de correo verificada de yahooinc.com
Shin MatsushimaThe University of TokyoDirección de correo verificada de ds.itc.u-tokyo.ac.jp
Hyokun YunMachine Learning Scientist at AmazonDirección de correo verificada de amazon.com
Zishun YuPhD student, University of Illinois ChicagoDirección de correo verificada de uic.edu

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Xinhua Zhang

University of Illinois Chicago

Dirección de correo verificada de uic.edu - Página principal

Machine Learning


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
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	96*	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	46	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
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	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	29	2021

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