Recursive support vector machines for dimensionality reduction Q Tao, D Chu, J Wang
IEEE Transactions on Neural Networks 19 (1), 189-193, 2008
85 2008 Stochastic coordinate descent methods for regularized smooth and nonsmooth losses Q Tao, K Kong, D Chu, G Wu
Machine Learning and Knowledge Discovery in Databases: European Conference …, 2012
20 2012 Stochastic learning via optimizing the variational inequalities Q Tao, QK Gao, DJ Chu, GW Wu
IEEE transactions on neural networks and learning systems 25 (10), 1769-1778, 2014
17 2014 Optimizing Top- Multiclass SVM via Semismooth Newton Algorithm D Chu, R Lu, J Li, X Yu, C Zhang, Q Tao
IEEE transactions on neural networks and learning systems 29 (12), 6264-6275, 2018
10 2018 A faster cutting plane algorithm with accelerated line search for linear SVM D Chu, C Zhang, Q Tao
Pattern Recognition 67, 127-138, 2017
9 2017 Improving Sparsity and Scalability in Regularized Nonconvex Truncated-Loss Learning Problems Q Tao, G Wu, D Chu
IEEE transactions on neural networks and learning systems 29 (7), 2782-2793, 2017
6 2017 Semismooth Newton Algorithm for Efficient Projections onto -norm Ball D Chu, C Zhang, S Sun, Q Tao
International Conference on Machine Learning, 1974-1983, 2020
5 2020 Survey of solving the optimization problems for sparse learning. Ruan Jian Xue Bao Q Tao, QK Gao, JY Jiang, DJ Chu
Journal of software 24 (11), 2498-2507, 2013
5 2013 Structured BFGS Method for Optimal Doubly Stochastic Matrix Approximation D Chu, C Zhang, S Sun, Q Tao
Proceedings of the AAAI Conference on Artificial Intelligence 37 (6), 7193-7201, 2023
2023 Coordinate Descent Algorithms for Large-Scale SVDD [J] Q TAO, Q LUO, YL ZHU, DJ CHU
Pattern Recognition and Artificial Intelligence 6, 2012
2012 The Recognition of Radar Trajectory Based on the Boosting Learning Algorithms X Liu, J Ding, D Chu, Q Tao
Danjian yu Zhidao Xuebao/ Journal of Projectiles, Rockets, Missiles and …, 2010
2010 求 AUC 优化 的对偶坐标下 方法 JY JIANG, Q TAO, QK GAO, DJ CHU