Qiang Wu - RankMe

48 papers B 1Journal 44Unranked 3

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