Wu, Qiang

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Sayan MukherjeeDuke University, MITVerified email at stat.duke.edu
Yiming YingProfessor, Department of Mathematics and Statistics, University at Albany, SUNYVerified email at albany.edu
Feng LiangDepartment of StatisticsVerified email at illinois.edu
Jun FanAssociate Professor, Hong Kong Baptist UniversityVerified email at hkbu.edu.hk
Yunlong FengState University of New York at AlbanyVerified email at albany.edu
Justin GuinneyTempusVerified email at tempus.com
Xin Guo 郭昕School of Mathematics and Physics, The University of QueenslandVerified email at uq.edu.au
Natesh S. PillaiHarvard UniversityVerified email at fas.harvard.edu
Robert L. WolpertProfessor of Statistical Science, Duke UniversityVerified email at duke.edu
song cuiMiddle Tennessee State UniversityVerified email at mtsu.edu
Mauro MaggioniBloomberg Distinguished Professor of Mathematics, and Applied Mathematics and StatisticsVerified email at jhu.edu
James M. HughesCACI Inc.Verified email at lgsinnovations.com
Massimiliano PontilIstituto Italiano di Tecnologia & University College LondonVerified email at iit.it
Lexin LiProfessor of Biostatistics, University of California, BerkeleyVerified email at berkeley.edu
Xin YangMiddle Tennessee State UniversityVerified email at mtsu.edu
Don HongProfessor of Mathematical Sciences, Middle Tennessee State UniversityVerified email at mtsu.edu
Yang WangSchool of Management, Northwestern Polytechnical UniversityVerified email at nwpu.edu.cn

Wu, Qiang

Middle Tennessee State University

Verified email at mtsu.edu - Homepage

Learning Theory Data Science High Dimensional Data Mining Big Data


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Support vector machine soft margin classifiers: error analysis DR Chen, Q Wu, Y Ying, DX Zhou Journal of Machine Learning Research 5 (Sep), 1143-1175, 2004	292	2004
Learning rates of least-square regularized regression Q Wu, Y Ying, DX Zhou Foundations of Computational Mathematics 6 (2), 171-192, 2006	262	2006
SVM soft margin classifiers: linear programming versus quadratic programming Q Wu, DX Zhou Neural computation 17 (5), 1160-1187, 2005	204	2005
Multi-kernel regularized classifiers Q Wu, Y Ying, DX Zhou Journal of Complexity 23 (1), 108-134, 2007	201	2007
Analysis of Support Vector Machine Classification. Q Wu, DX Zhou Journal of Computational Analysis & Applications 8 (2), 2006	131	2006
Learning with sample dependent hypothesis spaces Q Wu, DX Zhou Computers & Mathematics with Applications 56 (11), 2896-2907, 2008	108	2008
Least square regression with indefinite kernels and coefficient regularization H Sun, Q Wu Applied and Computational Harmonic Analysis 30 (1), 96-109, 2011	107	2011
Boundedness of commutators on Hardy type spaces S Lu, Q Wu, D Yang Science in China Series A: Mathematics 45 (8), 984-997, 2002	91	2002
Estimation of gradients and coordinate covariation in classification S Mukherjee, Q Wu Journal of Machine Learning Research 7 (Nov), 2481-2514, 2006	89	2006
Characterizing the function space for Bayesian kernel models NS Pillai, Q Wu, F Liang, S Mukherjee, RL Wolpert Journal of Machine Learning Research 8 (Aug), 1769-1797, 2007	82	2007
Learning theory approach to minimum error entropy criterion T Hu, J Fan, Q Wu, DX Zhou Journal of Machine Learning Research 14 (Feb), 377-397, 2013	75	2013
Regularization schemes for minimum error entropy principle T Hu, J Fan, Q Wu, DX Zhou Analysis and Applications 13 (04), 437-455, 2015	74	2015
Regularized least square regression with dependent samples H Sun, Q Wu Advances in Computational Mathematics 32 (2), 175-189, 2010	70	2010
Learning gradients on manifolds S Mukherjee, Q Wu, DX Zhou Bernoulli 16 (1), 181-207, 2010	63	2010
Localized sliced inverse regression Q Wu, S Mukherjee, F Liang Advances in neural information processing systems, 1785-1792, 2009	58	2009
Localized sliced inverse regression Q Wu, S Mukherjee, F Liang Advances in neural information processing systems, 1785-1792, 2009	58	2009
Application of integral operator for regularized least-square regression H Sun, Q Wu Mathematical and Computer Modelling 49 (1-2), 276-285, 2009	55	2009
Consistency analysis of an empirical minimum error entropy algorithm J Fan, T Hu, Q Wu, DX Zhou Applied and Computational Harmonic Analysis 41 (1), 164-189, 2016	53	2016
Empirical mode decomposition analysis for visual stylometry JM Hughes, D Mao, DN Rockmore, Y Wang, Q Wu IEEE transactions on pattern analysis and machine intelligence 34 (11), 2147 …, 2012	45	2012
Learning theory of distributed regression with bias corrected regularization kernel network ZC Guo, L Shi, Q Wu The Journal of Machine Learning Research 18 (1), 4237-4261, 2017	44	2017

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