Qiang Wu

Publication Activity (10 Years)

Years Active: 2004-2023
Publications (10 Years): 21

Top Topics

Top Venues

Math. Found. Comput.

J. Approx. Theory

IEEE Trans. Neural Networks Learn. Syst.

Publications

Donglin Wang, Don Hong, Qiang Wu
Attention Deficit Hyperactivity Disorder Classification Based on Deep Learning. IEEE ACM Trans. Comput. Biol. Bioinform. 20 (2) (2023)
Shouyou Huang, Yunlong Feng, Qiang Wu
Fast Rates of Gaussian Empirical Gain Maximization With Heavy-Tailed Noise. IEEE Trans. Neural Networks Learn. Syst. 33 (10) (2022)
Yunlong Feng, Qiang Wu
A statistical learning assessment of Huber regression. J. Approx. Theory 273 (2022)
Ting Hu, Qiang Wu, Ding-Xuan Zhou
Kernel gradient descent algorithm for information theoretic learning. J. Approx. Theory 263 (2021)
Shouyou Huang, Qiang Wu
Robust pairwise learning with Huber loss. J. Complex. 66 (2021)
Donglin Wang, Qiang Wu
On the Selection of Hyperparameters in Convolutional Neural Networks. CSCI (2021)
Yunlong Feng, Qiang Wu
A Framework of Learning Through Empirical Gain Maximization. Neural Comput. 33 (6) (2021)
Donglin Wang, Honglan Xu, Qiang Wu
Averaging versus voting: A comparative study of strategies for distributed classification. Math. Found. Comput. 3 (3) (2020)
Yunlong Feng, Qiang Wu
A Statistical Learning Assessment of Huber Regression. CoRR (2020)
Hongwei Sun, Qiang Wu
Optimal Rates of Distributed Regression with Imperfect Kernels. CoRR (2020)
Xin Guo, Lexin Li, Qiang Wu
Modeling interactive components by coordinate kernel polynomial models. Math. Found. Comput. 3 (4) (2020)
Yunlong Feng, Qiang Wu
A Framework of Learning Through Empirical Gain Maximization. CoRR (2020)
Xin Guo, Ting Hu, Qiang Wu
Distributed Minimum Error Entropy Algorithms. J. Mach. Learn. Res. 21 (2020)
Song Cui, Qiang Wu, James West, Jiangping Bai
Machine learning-based microarray analyses indicate low-expression genes might collectively influence PAH disease. PLoS Comput. Biol. 15 (8) (2019)
Ning Zhang, Qiang Wu
Online learning for supervised dimension reduction. Math. Found. Comput. 2 (2) (2019)
Ning Zhang, Zhou Yu, Qiang Wu
Overlapping Sliced Inverse Regression for Dimension Reduction. CoRR (2018)
Hongzhi Tong, Qiang Wu
Learning performance of regularized moving least square regression. J. Comput. Appl. Math. 325 (2017)
Zheng-Chu Guo, Lei Shi, Qiang Wu
Learning Theory of Distributed Regression with Bias Corrected Regularization Kernel Network. J. Mach. Learn. Res. 18 (2017)
Zheng-Chu Guo, Lei Shi, Qiang Wu
Learning Theory of Distributed Regression with Bias Corrected Regularization Kernel Network. CoRR (2017)
Qiang Wu
Bias corrected regularization kernel network and its applications. IJCNN (2017)
Ting Hu, Qiang Wu, Ding-Xuan Zhou
Convergence of Gradient Descent for Minimum Error Entropy Principle in Linear Regression. IEEE Trans. Signal Process. 64 (24) (2016)
Dong Mao, Yang Wang, Qiang Wu
A New Approach for Physiological Time Series. Adv. Data Sci. Adapt. Anal. 7 (1-2) (2015)
Hongwei Sun, Qiang Wu
Sparse Representation in Kernel Machines. IEEE Trans. Neural Networks Learn. Syst. 26 (10) (2015)
Dong Mao, Yang Wang, Qiang Wu
A new approach for physiological time series. CoRR (2015)
Xianfeng Hu, Yang Wang, Qiang Wu
Multiple authors Detection: a Quantitative Analysis of Dream of the Red Chamber. Adv. Data Sci. Adapt. Anal. 6 (4) (2014)
Xianfeng Hu, Yang Wang, Qiang Wu
Multiple Authors Detection: A Quantitative Analysis of Dream of the Red Chamber. CoRR (2014)
Jun Fan, Ting Hu, Qiang Wu, Ding-Xuan Zhou
Consistency Analysis of an Empirical Minimum Error Entropy Algorithm. CoRR (2014)
Ting Hu, Jun Fan, Qiang Wu, Ding-Xuan Zhou
Learning theory approach to minimum error entropy criterion. J. Mach. Learn. Res. 14 (1) (2013)
Qiang Wu
Regularization networks with indefinite kernels. J. Approx. Theory 166 (2013)
Yang Wang, Qiang Wu
Sparse PCA by iterative elimination algorithm. Adv. Comput. Math. 36 (1) (2012)
Ting Hu, Jun Fan, Qiang Wu, Ding-Xuan Zhou
Learning Theory Approach to Minimum Error Entropy Criterion CoRR (2012)
James Michael Hughes, Dong Mao, Daniel N. Rockmore, Yang Wang, Qiang Wu
Empirical Mode Decomposition Analysis for Visual Stylometry. IEEE Trans. Pattern Anal. Mach. Intell. 34 (11) (2012)
Yiming Ying, Qiang Wu, Colin Campbell
Learning the coordinate gradients. Adv. Comput. Math. 37 (3) (2012)
Justin Guinney, Qiang Wu, Sayan Mukherjee
Estimating variable structure and dependence in multitask learning via gradients. Mach. Learn. 83 (3) (2011)
Hongwei Sun, Qiang Wu
Regularized least square regression with dependent samples. Adv. Comput. Math. 32 (2) (2010)
Qiang Wu, Justin Guinney, Mauro Maggioni, Sayan Mukherjee
Learning Gradients: Predictive Models that Infer Geometry and Statistical Dependence. J. Mach. Learn. Res. 11 (2010)
Hongwei Sun, Qiang Wu
Application of integral operator for regularized least-square regression. Math. Comput. Model. 49 (1-2) (2009)
Qiang Wu, Ding-Xuan Zhou
Learning with sample dependent hypothesis spaces. Comput. Math. Appl. 56 (11) (2008)
Qiang Wu, Sayan Mukherjee, Feng Liang
Localized Sliced Inverse Regression. NIPS (2008)
Qiang Wu, Yiming Ying, Ding-Xuan Zhou
Multi-kernel regularized classifiers. J. Complex. 23 (1) (2007)
Natesh S. Pillai, Qiang Wu, Feng Liang, Sayan Mukherjee, Robert L. Wolpert
Characterizing the Function Space for Bayesian Kernel Models. J. Mach. Learn. Res. 8 (2007)
Sayan Mukherjee, Qiang Wu
Estimation of Gradients and Coordinate Covariation in Classification. J. Mach. Learn. Res. 7 (2006)
Qiang Wu, Yiming Ying, Ding-Xuan Zhou
Learning Rates of Least-Square Regularized Regression. Found. Comput. Math. 6 (2) (2006)
Qiang Wu, Ding-Xuan Zhou
SVM Soft Margin Classifiers: Linear Programming versus Quadratic Programming. Neural Comput. 17 (5) (2005)
Di-Rong Chen, Qiang Wu, Yiming Ying, Ding-Xuan Zhou
Support Vector Machine Soft Margin Classifiers: Error Analysis. J. Mach. Learn. Res. 5 (2004)