| Group sparse optimization via lp, q regularization Y Hu, C Li, K Meng, J Qin, X Yang Journal of Machine Learning Research 18 (1), 960-1011, 2017 | 139 | 2017 |
| Inferring gene regulatory networks by integrating ChIP-seq/chip and transcriptome data via LASSO-type regularization methods J Qin, Y Hu, F Xu, HK Yalamanchili, J Wang Methods 67 (3), 294-303, 2014 | 62 | 2014 |
| Linear convergence of CQ algorithms and applications in gene regulatory network inference J Wang, Y Hu, C Li, JC Yao Inverse Problems 33 (5), 055017, 2017 | 56 | 2017 |
| Inexact subgradient methods for quasi-convex optimization problems Y Hu, X Yang, CK Sim European Journal of Operational Research 240 (2), 315-327, 2015 | 54 | 2015 |
| On convergence rates of linearized proximal algorithms for convex composite optimization with applications Y Hu, C Li, X Yang SIAM Journal on Optimization 26 (2), 1207-1235, 2016 | 52 | 2016 |
| A general iterative approach for the system-level joint optimization of pavement maintenance, rehabilitation, and reconstruction planning L Zhang, L Fu, W Gu, Y Ouyang, Y Hu Transportation Research Part B: Methodological 105, 378-400, 2017 | 47 | 2017 |
| Integration of single-cell multi-omics for gene regulatory network inference X Hu, Y Hu, F Wu, RWT Leung, J Qin Computational and Structural Biotechnology Journal 18, 1925-1938, 2020 | 46 | 2020 |
| Extended Newton methods for multiobjective optimization: Majorizing function technique and convergence analysis J Wang, Y Hu, CK Wai Yu, C Li, X Yang SIAM Journal on Optimization 29 (3), 2388-2421, 2019 | 35 | 2019 |
| Stochastic subgradient method for quasi-convex optimization problems Y Hu, CKW Yu, C Li Journal of Nonlinear and Convex Analysis 17 (4), 711-724, 2016 | 27 | 2016 |
| A new linear convergence result for the iterative soft thresholding algorithm L Zhang, Y Hu, C Li, JC Yao Optimization 66 (7), 1177-1189, 2017 | 19 | 2017 |
| Conditional subgradient methods for constrained quasi-convex optimization problems Y Hu, CKW Yu, C Li, X Yang Journal of Nonlinear and Convex Analysis 17 (10), 2143-2158, 2016 | 19 | 2016 |
| A subgradient method based on gradient sampling for solving convex optimization problems Y Hu, CK Sim, X Yang Numerical Functional Analysis and Optimization 36 (12), 1559-1584, 2015 | 18 | 2015 |
| Nonconvex and nonsmooth sparse optimization via adaptively iterative reweighted methods H Wang, F Zhang, Y Shi, Y Hu Journal of Global Optimization, 1-32, 2021 | 17 | 2021 |
| Quasi-Slater and Farkas–Minkowski qualifications for semi-infinite programming with applications C Li, X Zhao, Y Hu SIAM Journal on Optimization 23 (4), 2208-2230, 2013 | 17 | 2013 |
| Incremental quasi-subgradient methods for minimizing the sum of quasi-convex functions Y Hu, CKW Yu, X Yang Journal of Global Optimization 75, 1003-1028, 2019 | 16 | 2019 |
| A family of projection gradient methods for solving the multiple-sets split feasibility problem J Wang, Y Hu, CKW Yu, X Zhuang Journal of Optimization Theory and Applications 183, 520-534, 2019 | 15 | 2019 |
| Dynamic demand-driven bike station clustering YJ Wang, YH Kuo, GQ Huang, W Gu, Y Hu Transportation Research Part E: Logistics and Transportation Review 160, 102656, 2022 | 14 | 2022 |
| Convergence rates of subgradient methods for quasi-convex optimization problems Y Hu, J Li, CKW Yu Computational Optimization and Applications 77 (1), 183-212, 2020 | 14 | 2020 |
| Abstract convergence theorem for quasi-convex optimization problems with applications CKW Yu, Y Hu, X Yang, SK Choy Optimization 68 (7), 1289-1304, 2019 | 12 | 2019 |
| Linear convergence of inexact descent method and inexact proximal gradient algorithms for lower-order regularization problems Y Hu, C Li, K Meng, X Yang Journal of Global Optimization 79 (4), 853-883, 2021 | 11 | 2021 |
Xiaoqi YangThe Hong Kong Polytechinc UniversityVerified email at polyu.edu.hk
