Lin, Chih-Jen

44 publications

NeurIPS 2025 Sampled Estimators for SoftMax Must Be Biased Li-Chung Lin, Yaxu Liu, Chih-Jen Lin

AAAI 2022 On the Use of Unrealistic Predictions in Hundreds of Papers Evaluating Graph Representations Li-Chung Lin, Cheng-Hung Liu, Chih-Ming Chen, Kai-Chin Hsu, I-Feng Wu, Ming-Feng Tsai, Chih-Jen Lin

JMLR 2021 A Two-Level Decomposition Framework Exploiting First and Second Order Information for SVM Training Problems Giulio Galvan, Matteo Lapucci, Chih-Jen Lin, Marco Sciandrone

JMLR 2019 The Common-Directions Method for Regularized Empirical Risk Minimization Po-Wei Wang, Ching-pei Lee, Chih-Jen Lin

ACML 2018 Preconditioned Conjugate Gradient Methods in Truncated Newton Frameworks for Large-Scale Linear Classification Chih-Yang Hsia, Wei-Lin Chiang, Chih-Jen Lin

ACML 2017 A Study on Trust Region Update Rules in Newton Methods for Large-Scale Linear Classification Chih-Yang Hsia, Ya Zhu, Chih-Jen Lin

AAAI 2017 A Unified Algorithm for One-Cass Structured Matrix Factorization with Side Information Hsiang-Fu Yu, Hsin-Yuan Huang, Inderjit S. Dhillon, Chih-Jen Lin

MLOSS 2016 LIBMF: A Library for Parallel Matrix Factorization in Shared-Memory Systems Wei-Sheng Chin, Bo-Wen Yuan, Meng-Yuan Yang, Yong Zhuang, Yu-Chin Juan, Chih-Jen Lin

JMLR 2015 Combination of Feature Engineering and Ranking Models for Paper-Author Identification in KDD Cup 2013 Chun-Liang Li, Yu-Chuan Su, Ting-Wei Lin, Cheng-Hao Tsai, Wei-Cheng Chang, Kuan-Hao Huang, Tzu-Ming Kuo, Shan-Wei Lin, Young-San Lin, Yu-Chen Lu, Chun-Pai Yang, Cheng-Xia Chang, Wei-Sheng Chin, Yu-Chin Juan, Hsiao-Yu Tung, Jui-Pin Wang, Cheng-Kuang Wei, Felix Wu, Tu-Chun Yin, Tong Yu, Yong Zhuang, Shou-de Lin, Hsuan-Tien Lin, Chih-Jen Lin

JMLR 2014 Effective String Processing and Matching for Author Disambiguation Wei-Sheng Chin, Yong Zhuang, Yu-Chin Juan, Felix Wu, Hsiao-Yu Tung, Tong Yu, Jui-Pin Wang, Cheng-Xia Chang, Chun-Pai Yang, Wei-Cheng Chang, Kuan-Hao Huang, Tzu-Ming Kuo, Shan-Wei Lin, Young-San Lin, Yu-Chen Lu, Yu-Chuan Su, Cheng-Kuang Wei, Tu-Chun Yin, Chun-Liang Li, Ting-Wei Lin, Cheng-Hao Tsai, Shou-De Lin, Hsuan-Tien Lin, Chih-Jen Lin

JMLR 2014 Iteration Complexity of Feasible Descent Methods for Convex Optimization Po-Wei Wang, Chih-Jen Lin

CVPR 2013 Dense Non-Rigid Point-Matching Using Random Projections Raffay Hamid, Dennis Decoste, Chih-Jen Lin

CVPR 2013 Large-Scale Video Summarization Using Web-Image Priors Aditya Khosla, Raffay Hamid, Chih-Jen Lin, Neel Sundaresan

JMLR 2012 An Improved GLMNET for L1-Regularized Logistic Regression Guo-Xun Yuan, Chia-Hua Ho, Chih-Jen Lin

JMLR 2012 Large-Scale Linear Support Vector Regression Chia-Hua Ho, Chih-Jen Lin

JMLR 2011 A Bayesian Approximation Method for Online Ranking Ruby C. Weng, Chih-Jen Lin

MLJ 2011 Dual Coordinate Descent Methods for Logistic Regression and Maximum Entropy Models Hsiang-Fu Yu, Fang-Lan Huang, Chih-Jen Lin

IJCAI 2011 Large Linear Classification When Data Cannot Fit in Memory Hsiang-Fu Yu, Cho-Jui Hsieh, Kai-Wei Chang, Chih-Jen Lin

JMLR 2010 A Comparison of Optimization Methods and Software for Large-Scale L1-Regularized Linear Classification Guo-Xun Yuan, Kai-Wei Chang, Cho-Jui Hsieh, Chih-Jen Lin

JMLR 2010 Iterative Scaling and Coordinate Descent Methods for Maximum Entropy Models Fang-Lan Huang, Cho-Jui Hsieh, Kai-Wei Chang, Chih-Jen Lin

JMLR 2010 Training and Testing Low-Degree Polynomial Data Mappings via Linear SVM Yin-Wen Chang, Cho-Jui Hsieh, Kai-Wei Chang, Michael Ringgaard, Chih-Jen Lin

ICML 2008 A Dual Coordinate Descent Method for Large-Scale Linear SVM Cho-Jui Hsieh, Kai-Wei Chang, Chih-Jen Lin, S. Sathiya Keerthi, S. Sundararajan

JMLR 2008 Coordinate Descent Method for Large-Scale L2-Loss Linear Support Vector Machines Kai-Wei Chang, Cho-Jui Hsieh, Chih-Jen Lin

MLOSS 2008 LIBLINEAR: A Library for Large Linear Classification Rong-En Fan, Kai-Wei Chang, Cho-Jui Hsieh, Xiang-Rui Wang, Chih-Jen Lin

ECML-PKDD 2008 Parallel Spectral Clustering Yangqiu Song, WenYen Chen, Hongjie Bai, Chih-Jen Lin, Edward Y. Chang

JMLR 2008 Ranking Individuals by Group Comparisons Tzu-Kuo Huang, Chih-Jen Lin, Ruby C. Weng

JMLR 2008 Trust Region Newton Method for Logistic Regression Chih-Jen Lin, Ruby C. Weng, S. Sathiya Keerthi

MLJ 2007 A Note on Platt's Probabilistic Outputs for Support Vector Machines Hsuan-Tien Lin, Chih-Jen Lin, Ruby C. Weng

ICML 2007 Trust Region Newton Methods for Large-Scale Logistic Regression Chih-Jen Lin, Ruby C. Weng, S. Sathiya Keerthi

JMLR 2006 Generalized Bradley-Terry Models and Multi-Class Probability Estimates Tzu-Kuo Huang, Ruby C. Weng, Chih-Jen Lin

ICML 2006 Ranking Individuals by Group Comparisons Tzu-Kuo Huang, Chih-Jen Lin, Ruby C. Weng

ALT 2005 Training Support Vector Machines via SMO-Type Decomposition Methods Pai-Hsuen Chen, Rong-En Fan, Chih-Jen Lin

JMLR 2005 Working Set Selection Using Second Order Information for Training Support Vector Machines Rong-En Fan, Pai-Hsuen Chen, Chih-Jen Lin

NeurIPS 2004 A Generalized Bradley-Terry Model: From Group Competition to Individual Skill Tzu-kuo Huang, Chih-jen Lin, Ruby C. Weng

NeCo 2004 Decomposition Methods for Linear Support Vector Machines Wei-Chun Kao, Kai-Min Chung, Chia-Liang Sun, Chih-Jen Lin

JMLR 2004 Probability Estimates for Multi-Class Classification by Pairwise Coupling Ting-Fan Wu, Chih-Jen Lin, Ruby C. Weng

NeCo 2003 Asymptotic Behaviors of Support Vector Machines with Gaussian Kernel S. Sathiya Keerthi, Chih-Jen Lin

NeurIPS 2003 Probability Estimates for Multi-Class Classification by Pairwise Coupling Ting-fan Wu, Chih-jen Lin, Ruby C. Weng

NeCo 2003 Radius Margin Bounds for Support Vector Machines with the RBF Kernel Kai-Min Chung, Wei-Chun Kao, Chia-Liang Sun, Li-Lun Wang, Chih-Jen Lin

NeCo 2002 A Note on the Decomposition Methods for Support Vector Regression Shuo-Peng Liao, Hsuan-Tien Lin, Chih-Jen Lin

MLJ 2002 A Simple Decomposition Method for Support Vector Machines Chih-Wei Hsu, Chih-Jen Lin

NeCo 2002 Training V -Support Vector Regression: Theory and Algorithms Chih-Chung Chang, Chih-Jen Lin

NeCo 2001 Formulations of Support Vector Machines: A Note from an Optimization Point of View Chih-Jen Lin

NeCo 2001 Training Nu-Support Vector Classifiers: Theory and Algorithms Chih-Chung Chang, Chih-Jen Lin