Ching-pei Lee - RankMe

32 papers A* 8A 3Journal 20Unranked 1

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	A Four-Operator Splitting Algorithm for Nonconvex and Nonsmooth Optimization. SIAM J. Optim. Jan Harold Alcantara, Ching-pei Lee, Akiko Takeda
2025	J	`jnl`	Global Convergence and Acceleration of Projection Methods for Feasibility Problems Involving Union Convex Sets. J. Optim. Theory Appl. Jan Harold Alcantara, Ching-pei Lee
2024	A*	`conf`	Accelerated Policy Gradient: On the Convergence Rates of the Nesterov Momentum for Reinforcement Learning. ICML Yen-Ju Chen, Nai-Chieh Huang, Ching-pei Lee, Ping-Chun Hsieh
2024	J	`jnl`	Accelerating Nuclear-norm Regularized Low-rank Matrix Optimization Through Burer-Monteiro Decomposition. J. Mach. Learn. Res. Ching-pei Lee, Ling Liang, Tianyun Tang, Kim-Chuan Toh
2024	A*	`conf`	Regularized Adaptive Momentum Dual Averaging with an Efficient Inexact Subproblem Solver for Training Structured Neural Network. NeurIPS Zih-Syuan Huang, Ching-pei Lee
2024	J	`jnl`	Regularized Adaptive Momentum Dual Averaging with an Efficient Inexact Subproblem Solver for Training Structured Neural Network. CoRR Zih-Syuan Huang, Ching-pei Lee
2023	J	`jnl`	Accelerating inexact successive quadratic approximation for regularized optimization through manifold identification. Math. Program. Ching-pei Lee
2022	A*	`conf`	Accelerated Projected Gradient Algorithms for Sparsity Constrained Optimization Problems. NeurIPS Jan Harold Alcantara, Ching-pei Lee
2022	J	`jnl`	Escaping Spurious Local Minima of Low-Rank Matrix Factorization Through Convex Lifting. CoRR Ching-pei Lee, Ling Liang, Tianyun Tang, Kim-Chuan Toh
2022	J	`jnl`	Limited-memory common-directions method for large-scale optimization: convergence, parallelization, and distributed optimization. Math. Program. Comput. Ching-pei Lee, Po-Wei Wang, Chih-Jen Lin
2022	A*	`conf`	Training Structured Neural Networks Through Manifold Identification and Variance Reduction. ICLR Zih-Syuan Huang, Ching-pei Lee
2021	J	`jnl`	Training Structured Neural Networks Through Manifold Identification and Variance Reduction. CoRR Zih-Syuan Huang, Ching-pei Lee
2020	J	`jnl`	Analyzing random permutations for cyclic coordinate descent. Math. Comput. Stephen J. Wright, Ching-pei Lee
2020	J	`jnl`	Distributed block-diagonal approximation methods for regularized empirical risk minimization. Mach. Learn. Ching-pei Lee, Kai-Wei Chang
2020	J	`jnl`	Inexact Variable Metric Stochastic Block-Coordinate Descent for Regularized Optimization. J. Optim. Theory Appl. Ching-pei Lee, Stephen J. Wright
2020	A*	`conf`	Manifold Identification for Ultimately Communication-Efficient Distributed Optimization. ICML Yu-Sheng Li, Wei-Lin Chiang, Ching-pei Lee
2019	J	`jnl`	A Distributed Quasi-Newton Algorithm for Primal and Dual Regularized Empirical Risk Minimization. CoRR Ching-pei Lee, Cong Han Lim, Stephen J. Wright
2019	A*	`conf`	First-Order Algorithms Converge Faster than $O(1/k)$ on Convex Problems. ICML Ching-pei Lee, Stephen J. Wright
2019	J	`jnl`	Inexact Successive quadratic approximation for regularized optimization. Comput. Optim. Appl. Ching-pei Lee, Stephen J. Wright
2019	J	`jnl`	Predicting kinase inhibitors using bioactivity matrix derived informer sets. PLoS Comput. Biol. Huikun Zhang, Spencer S. Ericksen, Ching-pei Lee, Gene E. Ananiev, Nathan Wlodarchak, Peng Yu, Julie C. Mitchell, Anthony Gitter, Stephen J. Wright, F. Michael Hoffmann, Scott A. Wildman, Michael A. Newton
2019	J	`jnl`	The Common-directions Method for Regularized Empirical Risk Minimization. J. Mach. Learn. Res. Po-Wei Wang, Ching-pei Lee, Chih-Jen Lin
2018	A*	`conf`	A Distributed Quasi-Newton Algorithm for Empirical Risk Minimization with Nonsmooth Regularization. KDD Ching-pei Lee, Cong Han Lim, Stephen J. Wright
2018	J	`jnl`	A Distributed Quasi-Newton Algorithm for Empirical Risk Minimization with Nonsmooth Regularization. CoRR Ching-pei Lee, Cong Han Lim, Stephen J. Wright
2018	A	`conf`	Limited-memory Common-directions Method for Distributed Ll-regularized Linear Classification. SDM Wei-Lin Chiang, Yu-Sheng Li, Ching-pei Lee, Chih-Jen Lin
2017	A	`conf`	Limited-memory Common-directions Method for Distributed Optimization and its Application on Empirical Risk Minimization. SDM Ching-pei Lee, Po-Wei Wang, Weizhu Chen, Chih-Jen Lin
2017	J	`jnl`	Using Neural Networks to Detect Line Outages from PMU Data. CoRR Ching-pei Lee, Stephen J. Wright
2015	A*	`conf`	Distributed Box-Constrained Quadratic Optimization for Dual Linear SVM. ICML Ching-pei Lee, Dan Roth
2015	J	`jnl`	Distributed Training of Structured SVM. CoRR Ching-pei Lee, Kai-Wei Chang, Shyam Upadhyay, Dan Roth
2014	J	`jnl`	Large-Scale Linear RankSVM. Neural Comput. Ching-pei Lee, Chih-Jen Lin
2014	A	`conf`	Large-scale Kernel RankSVM. SDM Tzu-Ming Kuo, Ching-pei Lee, Chih-Jen Lin
2014	—	`conf`	Large-scale logistic regression and linear support vector machines using spark. IEEE BigData Chieh-Yen Lin, Cheng-Hao Tsai, Ching-pei Lee, Chih-Jen Lin
2013	J	`jnl`	A Study on L2-Loss (Squared Hinge-Loss) Multiclass SVM. Neural Comput. Ching-pei Lee, Chih-Jen Lin