Ching-Pei Lee

According to our database, Ching-Pei Lee authored at least 13 papers between 2013 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Accelerating inexact successive quadratic approximation for regularized optimization through manifold identification.

Ching-Pei Lee

Math. Program., 2023

2022

Limited-memory common-directions method for large-scale optimization: convergence, parallelization, and distributed optimization.

Ching-Pei Lee, Po-Wei Wang, Chih-Jen Lin

Math. Program. Comput., 2022

2020

Distributed block-diagonal approximation methods for regularized empirical risk minimization.

Ching-Pei Lee, Kai-Wei Chang

Mach. Learn., 2020

Manifold Identification for Ultimately Communication-Efficient Distributed Optimization.

Yu-Sheng Li, Wei-Lin Chiang, Ching-Pei Lee

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

The Common-directions Method for Regularized Empirical Risk Minimization.

Po-Wei Wang, Ching-Pei Lee, Chih-Jen Lin

J. Mach. Learn. Res., 2019

2018

Limited-memory Common-directions Method for Distributed Ll-regularized Linear Classification.

Wei-Lin Chiang, Yu-Sheng Li, Ching-Pei Lee, Chih-Jen Lin

Proceedings of the 2018 SIAM International Conference on Data Mining, 2018

2017

Limited-memory Common-directions Method for Distributed Optimization and its Application on Empirical Risk Minimization.

Ching-Pei Lee, Po-Wei Wang, Weizhu Chen, Chih-Jen Lin

Proceedings of the 2017 SIAM International Conference on Data Mining, 2017

2015

Distributed Training of Structured SVM.

Ching-Pei Lee, Kai-Wei Chang, Shyam Upadhyay, Dan Roth

CoRR, 2015

Distributed Box-Constrained Quadratic Optimization for Dual Linear SVM.

Ching-Pei Lee, Dan Roth

Proceedings of the 32nd International Conference on Machine Learning, 2015

2014

Large-Scale Linear RankSVM.

Ching-Pei Lee, Chih-Jen Lin

Neural Comput., 2014

Large-scale Kernel RankSVM.

Tzu-Ming Kuo, Ching-Pei Lee, Chih-Jen Lin

Proceedings of the 2014 SIAM International Conference on Data Mining, 2014

Large-scale logistic regression and linear support vector machines using spark.

Chieh-Yen Lin, Cheng-Hao Tsai, Ching-Pei Lee, Chih-Jen Lin

Proceedings of the 2014 IEEE International Conference on Big Data (IEEE BigData 2014), 2014

2013

A Study on L2-Loss (Squared Hinge-Loss) Multiclass SVM.

Ching-Pei Lee, Chih-Jen Lin

Neural Comput., 2013