Year |
Citation |
Score |
2020 |
Chirstmann A, Wu Q, Zhou D. Preface to the special issue on analysis in machine learning and data science Communications On Pure and Applied Analysis. 19. DOI: 10.3934/Cpaa.2020171 |
0.309 |
|
2020 |
Tong H, Wu Q. Moving quantile regression Journal of Statistical Planning and Inference. 205: 46-63. DOI: 10.1016/J.Jspi.2019.06.003 |
0.363 |
|
2020 |
Feng Y, Wu Q. Learning under (1 + ϵ)-moment conditions Applied and Computational Harmonic Analysis. 49: 495-520. DOI: 10.1016/J.Acha.2020.05.009 |
0.336 |
|
2020 |
Hu T, Wu Q, Zhou D. Distributed kernel gradient descent algorithm for minimum error entropy principle Applied and Computational Harmonic Analysis. 49: 229-256. DOI: 10.1016/J.Acha.2019.01.002 |
0.311 |
|
2019 |
Cui S, Wu Q, West J, Bai J. Machine learning-based microarray analyses indicate low-expression genes might collectively influence PAH disease. Plos Computational Biology. 15: e1007264. PMID 31404060 DOI: 10.1371/journal.pcbi.1007264 |
0.329 |
|
2016 |
Yang X, Wu Q, Zou J, Hong D. Spatial Regularization for Multitask Learning and Application in fMRI Data Analysis British Journal of Mathematics & Computer Science. 14: 1-13. DOI: 10.9734/Bjmcs/2016/23829 |
0.318 |
|
2016 |
Micchelli CA, Pontil M, Wu Q, Zhou D. Error bounds for learning the kernel Analysis and Applications. 14: 849-868. DOI: 10.1142/S0219530516400054 |
0.36 |
|
2016 |
Fan J, Hu T, Wu Q, Zhou DX. Consistency analysis of an empirical minimum error entropy algorithm Applied and Computational Harmonic Analysis. 41: 164-189. DOI: 10.1016/j.acha.2014.12.005 |
0.339 |
|
2015 |
Sun H, Wu Q. Sparse Representation in Kernel Machines. Ieee Transactions On Neural Networks and Learning Systems. PMID 25643413 DOI: 10.1109/TNNLS.2014.2375209 |
0.357 |
|
2015 |
Hu T, Fan J, Wu Q, Zhou D. Regularization schemes for minimum error entropy principle Analysis and Applications. 13: 437-455. DOI: 10.1142/S0219530514500110 |
0.355 |
|
2014 |
Hu X, Wang Y, Wu Q. Multiple Authors Detection: A Quantitative Analysis Of Dream Of The Red Chamber Advances in Adaptive Data Analysis. 6: 1450012. DOI: 10.1142/S1793536914500125 |
0.307 |
|
2013 |
Wu Q, Liang F, Mukherjee S. Kernel sliced inverse regression: Regularization and consistency Abstract and Applied Analysis. 2013. DOI: 10.1155/2013/540725 |
0.552 |
|
2013 |
Sun H, Wu Q. Indefinite Kernel Network With Dependent Sampling Analysis and Applications. 11: 1350020. DOI: 10.1142/S0219530513500206 |
0.342 |
|
2012 |
Ying Y, Wu Q, Campbell C. Learning the coordinate gradients Advances in Computational Mathematics. 37: 355-378. DOI: 10.1007/S10444-011-9211-6 |
0.352 |
|
2012 |
Wang Y, Wu Q. Sparse PCA by iterative elimination algorithm Advances in Computational Mathematics. 36: 137-151. DOI: 10.1007/S10444-011-9186-3 |
0.312 |
|
2011 |
Sun H, Wu Q. Least square regression with indefinite kernels and coefficient regularization Applied and Computational Harmonic Analysis. 30: 96-109. DOI: 10.1016/J.Acha.2010.04.001 |
0.367 |
|
2011 |
Guinney J, Wu Q, Mukherjee S. Estimating variable structure and dependence in multitask learning via gradients Machine Learning. 83: 265-287. DOI: 10.1007/S10994-010-5217-4 |
0.588 |
|
2010 |
Mukherjee S, Wu Q, Zhou DX. Learning gradients on manifolds Bernoulli. 16: 181-207. DOI: 10.3150/09-BEJ206 |
0.57 |
|
2010 |
Wu Q, Liang F, Mukherjee S. Localized sliced inverse regression Journal of Computational and Graphical Statistics. 19: 843-860. DOI: 10.1198/jcgs.2010.08080 |
0.567 |
|
2010 |
Sun H, Wu Q. Regularized least square regression with dependent samples Advances in Computational Mathematics. 32: 175-189. DOI: 10.1007/S10444-008-9099-Y |
0.335 |
|
2009 |
Sun H, Wu Q. Application of integral operator for regularized least-square regression Mathematical and Computer Modelling. 49: 276-285. DOI: 10.1016/J.Mcm.2008.08.005 |
0.321 |
|
2009 |
Sun H, Wu Q. A note on application of integral operator in learning theory Applied and Computational Harmonic Analysis. 26: 416-421. DOI: 10.1016/J.Acha.2008.10.002 |
0.35 |
|
2008 |
Wu Q, Zhou D. Learning with sample dependent hypothesis spaces Computers & Mathematics With Applications. 56: 2896-2907. DOI: 10.1016/J.Camwa.2008.09.014 |
0.355 |
|
2007 |
Wu Q, Ying Y, Zhou DX. Multi-kernel regularized classifiers Journal of Complexity. 23: 108-134. DOI: 10.1016/j.jco.2006.06.007 |
0.315 |
|
2006 |
Wu Q, Ying Y, Zhou DX. Learning Theory: From Regression to Classification Studies in Computational Mathematics. 12: 257-290. DOI: 10.1016/S1570-579X(06)80011-X |
0.342 |
|
2006 |
Wu Q, Ying Y, Zhou DX. Learning rates of least-square regularized regression Foundations of Computational Mathematics. 6: 171-192. DOI: 10.1007/s10208-004-0155-9 |
0.373 |
|
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