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LEE Ching-pei
LEE Ching-pei
Institute of Statistical Mathematics
Подтвержден адрес электронной почты в домене ism.ac.jp - Главная страница
Название
Процитировано
Процитировано
Год
Large-scale linear ranksvm
CP Lee, CJ Lin
Neural computation 26 (4), 781-817, 2014
1532014
Large-scale logistic regression and linear support vector machines using spark
CY Lin, CH Tsai, CP Lee, CJ Lin
2014 IEEE International Conference on Big Data (Big Data), 519-528, 2014
1172014
A study on L2-loss (squared hinge-loss) multiclass SVM
CP Lee, CJ Lin
Neural computation 25 (5), 1302-1323, 2013
842013
A revisit to support vector data description
WC Chang, CP Lee, CJ Lin
Dept. Comput. Sci., Nat. Taiwan Univ., Taipei, Taiwan, Tech. Rep, 2013
842013
Distributed box-constrained quadratic optimization for dual linear SVM
CP Lee, D Roth
International Conference on Machine Learning, 987-996, 2015
642015
Random permutations fix a worst case for cyclic coordinate descent
CP Lee, SJ Wright
IMA Journal of Numerical Analysis 39 (3), 1246-1275, 2019
492019
Large-scale kernel ranksvm
TM Kuo, CP Lee, CJ Lin
Proceedings of the 2014 SIAM international conference on data mining, 812-820, 2014
482014
Inexact successive quadratic approximation for regularized optimization
C Lee, SJ Wright
Computational Optimization and Applications 72, 641-674, 2019
422019
Analyzing random permutations for cyclic coordinate descent
S Wright, C Lee
Mathematics of Computation 89, 2217-2248, 2020
302020
A distributed quasi-Newton algorithm for empirical risk minimization with nonsmooth regularization
C Lee, CH Lim, SJ Wright
Proceedings of the 24th ACM SIGKDD international conference on knowledge …, 2018
292018
Limited-memory common-directions method for distributed optimization and its application on empirical risk minimization
CP Lee, PW Wang, W Chen, CJ Lin
Proceedings of the 2017 SIAM International Conference on Data Mining, 732-740, 2017
162017
Accelerating Inexact Successive Quadratic Approximation for Regularized Optimization Through Manifold Identification
C Lee
mathematical Programming, 2023
152023
Distributed block-diagonal approximation methods for regularized empirical risk minimization
C Lee, KW Chang
Machine Learning 109 (4), 813-852, 2020
122020
First-Order Algorithms Converge Faster than on Convex Problems
CP Lee, S Wright
International Conference on Machine Learning, 3754-3762, 2019
112019
The common-directions method for regularized empirical risk minimization
PW Wang, C Lee, CJ Lin
The Journal of Machine Learning Research 20 (1), 2072-2120, 2019
102019
Distributed training of structured SVM
C Lee, KW Chang, S Upadhyay, D Roth
NIPS Workshop on Optimization for Machine Learning, 2015
102015
Using neural networks to detect line outages from PMU data
C Lee, SJ Wright
arXiv preprint arXiv:1710.05916, 2017
82017
Training Structured Neural Networks Through Manifold Identification and Variance Reduction
ZS Huang, C Lee
The 10th International Conference on Learning Representations, 2021
72021
Manifold Identification for Ultimately Communication-Efficient Distributed Optimization
YS Li, WL Chiang, C Lee
International Conference on Machine Learning, 2020
52020
Limited-memory Common-directions Method for Large-scale Optimization: Convergence, Parallelization, and Distributed Optimization
C Lee, PW Wang, CJ Lin
Mathematical Programming Computation, 2022
42022
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