Chih-Jen Lin

150 papers A* 24A 18B 5C 2Journal 78Unranked 21
YearRankTypeTitle / Venue / Authors
2026 J jnl
A Geometry-Aware Efficient Algorithm for Compositional Entropic Risk Minimization.
CoRR
Xiyuan Wei, Linli Zhou, Bokun Wang, Chih-Jen Lin, Tianbao Yang
2025 J jnl
NeuCLIP: Efficient Large-Scale CLIP Training with Neural Normalizer Optimization.
CoRR
Xiyuan Wei, Chih-Jen Lin, Tianbao Yang
2025 J jnl
One-Class SVM Probabilistic Outputs.
IEEE Trans. Neural Networks Learn. Syst.
Zhongyi Que, Chih-Jen Lin
2025 — conf
Preserving Zero-shot Capability in Supervised Fine-tuning for Multi-label Text Classification.
NAACL (Findings)
Si-An Chen, Hsuan-Tien Lin, Chih-Jen Lin
2025 A* conf
Revisiting One-Versus-One and One-Versus-Rest: Insights into Imbalanced Multi-Class Classification.
ICDM
Kuan-Ting Chen, Chih-Jen Lin
2025 A conf
SparseKmeans: Efficient K-means Clustering For Sparse Data.
CIKM
Khoi Nguyen Pham Dang, He-Zhe Lin, Chih-Jen Lin
2024 J jnl
A Step-by-step Introduction to the Implementation of Automatic Differentiation.
CoRR
Yu-Hsueh Fang, He-Zhe Lin, Jie-Jyun Liu, Chih-Jen Lin
2024 A* conf
Exploring Space Efficiency in a Tree-based Linear Model for Extreme Multi-label Classification.
EMNLP
He-Zhe Lin, Cheng-Hung Liu, Chih-Jen Lin
2024 J jnl
Exploring space efficiency in a tree-based linear model for extreme multi-label classification.
CoRR
He-Zhe Lin, Cheng-Hung Liu, Chih-Jen Lin
2024 A conf
One-class Matrix Factorization: Point-Wise Regression-Based or Pair-Wise Ranking-Based?
RecSys
Sheng-Wei Chen, Chih-Jen Lin
2024 — conf
Random Label Forests: An Ensemble Method with Label Subsampling For Extreme Multi-Label Problems.
EMNLP (Findings)
Sheng-Wei Chen, Chih-Jen Lin
2023 — conf
Linear Classifier: An Often-Forgotten Baseline for Text Classification.
ACL (2)
Yu-Chen Lin, Si-An Chen, Jie-Jyun Liu, Chih-Jen Lin
2023 J jnl
Linear Classifier: An Often-Forgotten Baseline for Text Classification.
CoRR
Yu-Chen Lin, Si-An Chen, Jie-Jyun Liu, Chih-Jen Lin
2023 J jnl
Mimic-IV-ICD: A new benchmark for eXtreme MultiLabel Classification.
CoRR
Thanh-Tung Nguyen, Viktor Schlegel, Abhinav Ramesh Kashyap, Stefan Winkler, Shao-Syuan Huang, Jie-Jyun Liu, Chih-Jen Lin
2023 A* conf
On the "Rough Use" of Machine Learning Techniques.
SIGIR
Chih-Jen Lin
2023 A conf
On the Thresholding Strategy for Infrequent Labels in Multi-label Classification.
CIKM
Yu-Jen Lin, Chih-Jen Lin
2022 J jnl
A Study on Truncated Newton Methods for Linear Classification.
IEEE Trans. Neural Networks Learn. Syst.
Leonardo Galli, Chih-Jen Lin
2022 — conf
Even the Simplest Baseline Needs Careful Re-investigation: A Case Study on XML-CNN.
NAACL-HLT
Si-An Chen, Jie-Jyun Liu, Tsung-Han Yang, Hsuan-Tien Lin, Chih-Jen Lin
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
On the Use of Unrealistic Predictions in Hundreds of Papers Evaluating Graph Representations.
AAAI
Li-Chung Lin, Cheng-Hung Liu, Chih-Ming Chen, Kai-Chin Hsu, I-Feng Wu, Ming-Feng Tsai, Chih-Jen Lin
2022 A* conf
Practical Counterfactual Policy Learning for Top-K Recommendations.
KDD
Yaxu Liu, Jui-Nan Yen, Bo-Wen Yuan, Rundong Shi, Peng Yan, Chih-Jen Lin
2021 J jnl
A Two-Level Decomposition Framework Exploiting First and Second Order Information for SVM Training Problems.
J. Mach. Learn. Res.
Giulio Galvan, Matteo Lapucci, Chih-Jen Lin, Marco Sciandrone
2021 A* conf
Efficient Optimization Methods for Extreme Similarity Learning with Nonlinear Embeddings.
KDD
Bo-Wen Yuan, Yu-Sheng Li, Pengrui Quan, Chih-Jen Lin
2021 A* conf
Limited-memory Common-directions Method With Subsampled Newton Directions for Large-scale Linear Classification.
ICDM
Jui-Nan Yen, Chih-Jen Lin
2021 J jnl
On the Use of Unrealistic Predictions in Hundreds of Papers Evaluating Graph Representations.
CoRR
Li-Chung Lin, Cheng-Hung Liu, Chih-Ming Chen, Kai-Chin Hsu, I-Feng Wu, Ming-Feng Tsai, Chih-Jen Lin
2021 — conf
Parameter Selection: Why We Should Pay More Attention to It.
ACL/IJCNLP (2)
Jie-Jyun Liu, Tsung-Han Yang, Si-An Chen, Chih-Jen Lin
2021 J jnl
Parameter Selection: Why We Should Pay More Attention to It.
CoRR
Jie-Jyun Liu, Tsung-Han Yang, Si-An Chen, Chih-Jen Lin
2020 J jnl
An Efficient Newton Method for Extreme Similarity Learning with Nonlinear Embeddings.
CoRR
Bo-Wen Yuan, Yu-Sheng Li, Pengrui Quan, Chih-Jen Lin
2020 B conf
AutoConjunction: Adaptive Model-based Feature Conjunction for CTR Prediction.
MDM
Chih-Yao Chang, Xing Tang, Bo-Wen Yuan, Jui-Yang Hsia, Zhirong Liu, Zhenhua Dong, Xiuqiang He, Chih-Jen Lin
2020 A conf
Dual Coordinate-Descent Methods for Linear One-Class SVM and SVDD.
SDM
Hung-Yi Chou, Pin-Yen Lin, Chih-Jen Lin
2020 J jnl
Introduction to the Special Issue on the Best Papers from KDD 2018.
ACM Trans. Knowl. Discov. Data
Hui Xiong, Chih-Jen Lin
2020 J jnl
Newton Methods for Convolutional Neural Networks.
ACM Trans. Intell. Syst. Technol.
Chien-Chih Wang, Kent Loong Tan, Chih-Jen Lin
2020 J jnl
Parameter Selection for Linear Support Vector Regression.
IEEE Trans. Neural Networks Learn. Syst.
Jui-Yang Hsia, Chih-Jen Lin
2020 A conf
Two-variable Dual Coordinate Descent Methods for Linear SVM with/without the Bias Term.
SDM
Chi-Cheng Chiu, Pin-Yen Lin, Chih-Jen Lin
2020 A conf
Unbiased Ad Click Prediction for Position-aware Advertising Systems.
RecSys
Bo-Wen Yuan, Yaxu Liu, Jui-Yang Hsia, Zhenhua Dong, Chih-Jen Lin
2019 A conf
Improving Ad Click Prediction by Considering Non-displayed Events.
CIKM
Bo-Wen Yuan, Jui-Yang Hsia, Mengyuan Yang, Hong Zhu, Chih-Yao Chang, Zhenhua Dong, Chih-Jen Lin
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 J jnl
An Efficient Alternating Newton Method for Learning Factorization Machines.
ACM Trans. Intell. Syst. Technol.
Wei-Sheng Chin, Bo-Wen Yuan, Mengyuan Yang, Chih-Jen Lin
2018 J jnl
Distributed Newton Methods for Deep Neural Networks.
CoRR
Chien-Chih Wang, Kent Loong Tan, Chun-Ting Chen, Yu-Hsiang Lin, S. Sathiya Keerthi, Dhruv Mahajan, S. Sundararajan, Chih-Jen Lin
2018 J jnl
Distributed Newton Methods for Deep Neural Networks.
Neural Comput.
Chien-Chih Wang, Kent Loong Tan, Chun-Ting Chen, Yu-Hsiang Lin, S. Sathiya Keerthi, Dhruv Mahajan, S. Sundararajan, Chih-Jen Lin
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
2018 A conf
Naive Parallelization of Coordinate Descent Methods and an Application on Multi-core L1-regularized Classification.
CIKM
Yong Zhuang, Yu-Chin Juan, Guo-Xun Yuan, Chih-Jen Lin
2018 J jnl
Newton Methods for Convolutional Neural Networks.
CoRR
Chien-Chih Wang, Kent Loong Tan, Chih-Jen Lin
2018 C conf
Preconditioned Conjugate Gradient Methods in Truncated Newton Frameworks for Large-scale Linear Classification.
ACML
Chih-Yang Hsia, Wei-Lin Chiang, Chih-Jen Lin
2017 C conf
A Study on Trust Region Update Rules in Newton Methods for Large-scale Linear Classification.
ACML
Chih-Yang Hsia, Ya Zhu, Chih-Jen Lin
2017 A* conf
A Unified Algorithm for One-Cass Structured Matrix Factorization with Side Information.
AAAI
Hsiang-Fu Yu, Hsin-Yuan Huang, Inderjit S. Dhillon, 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 A conf
Selection of Negative Samples for One-class Matrix Factorization.
SDM
Hsiang-Fu Yu, Mikhail Bilenko, Chih-Jen Lin
2016 A conf
Field-aware Factorization Machines for CTR Prediction.
RecSys
Yu-Chin Juan, Yong Zhuang, Wei-Sheng Chin, Chih-Jen Lin
2016 J jnl
LIBMF: A Library for Parallel Matrix Factorization in Shared-memory Systems.
J. Mach. Learn. Res.
Wei-Sheng Chin, Bo-Wen Yuan, Mengyuan Yang, Yong Zhuang, Yu-Chin Juan, Chih-Jen Lin
2016 A conf
Linear and Kernel Classification: When to Use Which?
SDM
Hsin-Yuan Huang, Chih-Jen Lin
2016 A* conf
Parallel Dual Coordinate Descent Method for Large-scale Linear Classification in Multi-core Environments.
KDD
Wei-Lin Chiang, Mu-Chu Lee, Chih-Jen Lin
2015 J jnl
A Fast Parallel Stochastic Gradient Method for Matrix Factorization in Shared Memory Systems.
ACM Trans. Intell. Syst. Technol.
Wei-Sheng Chin, Yong Zhuang, Yu-Chin Juan, Chih-Jen Lin
2015 — conf
A Learning-Rate Schedule for Stochastic Gradient Methods to Matrix Factorization.
PAKDD (1)
Wei-Sheng Chin, Yong Zhuang, Yu-Chin Juan, Chih-Jen Lin
2015 J jnl
Combination of feature engineering and ranking models for paper-author identification in KDD cup 2013.
J. Mach. Learn. Res.
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
2015 — conf
Distributed Newton Methods for Regularized Logistic Regression.
PAKDD (2)
Yong Zhuang, Wei-Sheng Chin, Yu-Chin Juan, Chih-Jen Lin
2015 A* conf
Fast Matrix-Vector Multiplications for Large-Scale Logistic Regression on Shared-Memory Systems.
ICDM
Mu-Chu Lee, Wei-Lin Chiang, Chih-Jen Lin
2015 J jnl
Subsampled Hessian Newton Methods for Supervised Learning.
Neural Comput.
Chien-Chih Wang, Chun-Heng Huang, Chih-Jen Lin
2015 A* conf
Warm Start for Parameter Selection of Linear Classifiers.
KDD
Bo-Yu Chu, Chia-Hua Ho, Cheng-Hao Tsai, Chieh-Yen Lin, Chih-Jen Lin
2014 J jnl
Big Data Small Footprint: The Design of A Low-Power Classifier for Detecting Transportation Modes.
Proc. VLDB Endow.
Meng-Chieh Yu, Tong Yu, Shao-Chen Wang, Chih-Jen Lin, Edward Y. Chang
2014 J jnl
Effective string processing and matching for author disambiguation.
J. Mach. Learn. Res.
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
2014 A* conf
Incremental and decremental training for linear classification.
KDD
Cheng-Hao Tsai, Chieh-Yen Lin, Chih-Jen Lin
2014 J jnl
Iteration complexity of feasible descent methods for convex optimization.
J. Mach. Learn. Res.
Po-Wei Wang, Chih-Jen Lin
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
2014 — ch.
Support Vector Machines.
Data Classification: Algorithms and Applications
Po-Wei Wang, Chih-Jen Lin
2013 J jnl
A Study on L2-Loss (Squared Hinge-Loss) Multiclass SVM.
Neural Comput.
Ching-pei Lee, Chih-Jen Lin
2013 A conf
A fast parallel SGD for matrix factorization in shared memory systems.
RecSys
Yong Zhuang, Wei-Sheng Chin, Yu-Chin Juan, Chih-Jen Lin
2013 — conf
Combination of feature engineering and ranking models for paper-author identification in KDD Cup 2013.
KDD Cup
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
2013 A* conf
Dense Non-rigid Point-Matching Using Random Projections.
CVPR
Raffay Hamid, Dennis DeCoste, Chih-Jen Lin
2013 — conf
Effective string processing and matching for author disambiguation.
KDD Cup
Wei-Sheng Chin, Yu-Chin Juan, Yong Zhuang, 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
2013 A* conf
Large-Scale Video Summarization Using Web-Image Priors.
CVPR
Aditya Khosla, Raffay Hamid, Chih-Jen Lin, Neel Sundaresan
2012 — conf
A Linear Ensemble of Individual and Blended Models for Music Rating Prediction.
KDD Cup
Po-Lung Chen, Chen-Tse Tsai, Yao-Nan Chen, Ku-Chun Chou, Chun-Liang Li, Cheng-Hao Tsai, Kuan-Wei Wu, Yu-Cheng Chou, Chung-Yi Li, Wei-Shih Lin, Shu-Hao Yu, Rong-Bing Chiu, Chieh-Yen Lin, Chien-Chih Wang, Po-Wei Wang, Wei-Lun Su, Chen-Hung Wu, Tsung-Ting Kuo, Todd G. McKenzie, Ya-Hsuan Chang, Chun-Sung Ferng, Chia-Mau Ni, Hsuan-Tien Lin, Chih-Jen Lin, Shou-De Lin
2012 J jnl
An Improved GLMNET for L1-regularized Logistic Regression.
J. Mach. Learn. Res.
Guo-Xun Yuan, Chia-Hua Ho, Chih-Jen Lin
2012 A* conf
Experiences and lessons in developing industry-strength machine learning and data mining software.
KDD
Chih-Jen Lin
2012 J jnl
Large Linear Classification When Data Cannot Fit in Memory.
ACM Trans. Knowl. Discov. Data
Hsiang-Fu Yu, Cho-Jui Hsieh, Kai-Wei Chang, Chih-Jen Lin
2012 J jnl
Large-scale linear support vector regression.
J. Mach. Learn. Res.
Chia-Hua Ho, Chih-Jen Lin
2012 — conf
Novel Models and Ensemble Techniques to Discriminate Favorite Items from Unrated Ones for Personalized Music Recommendation.
KDD Cup
Todd G. McKenzie, Chun-Sung Ferng, Yao-Nan Chen, Chun-Liang Li, Cheng-Hao Tsai, Kuan-Wei Wu, Ya-Hsuan Chang, Chung-Yi Li, Wei-Shih Lin, Shu-Hao Yu, Chieh-Yen Lin, Po-Wei Wang, Chia-Mau Ni, Wei-Lun Su, Tsung-Ting Kuo, Chen-Tse Tsai, Po-Lung Chen, Rong-Bing Chiu, Ku-Chun Chou, Yu-Cheng Chou, Chien-Chih Wang, Chen-Hung Wu, Hsuan-Tien Lin, Chih-Jen Lin, Shou-De Lin
2012 J jnl
Recent Advances of Large-Scale Linear Classification.
Proc. IEEE
Guo-Xun Yuan, Chia-Hua Ho, Chih-Jen Lin
2011 J jnl
A Bayesian Approximation Method for Online Ranking.
J. Mach. Learn. Res.
Ruby C. Weng, Chih-Jen Lin
2011 A* conf
An improved GLMNET for l1-regularized logistic regression.
KDD
Guo-Xun Yuan, Chia-Hua Ho, Chih-Jen Lin
2011 J jnl
Dual coordinate descent methods for logistic regression and maximum entropy models.
Mach. Learn.
Hsiang-Fu Yu, Fang-Lan Huang, Chih-Jen Lin
2011 J jnl
LIBSVM: A library for support vector machines.
ACM Trans. Intell. Syst. Technol.
Chih-Chung Chang, Chih-Jen Lin
2011 A* conf
Large Linear Classification When Data Cannot Fit in Memory.
IJCAI
Hsiang-Fu Yu, Cho-Jui Hsieh, Kai-Wei Chang, Chih-Jen Lin
2011 J jnl
Parallel Spectral Clustering in Distributed Systems.
IEEE Trans. Pattern Anal. Mach. Intell.
Wen-Yen Chen, Yangqiu Song, Hongjie Bai, Chih-Jen Lin, Edward Y. Chang
2010 J jnl
A Comparison of Optimization Methods and Software for Large-scale L1-regularized Linear Classification.
J. Mach. Learn. Res.
Guo-Xun Yuan, Kai-Wei Chang, Cho-Jui Hsieh, Chih-Jen Lin
2010 B conf
Active learning strategies using SVMs.
IJCNN
Ming-Hen Tsai, Chia-Hua Ho, Chih-Jen Lin
2010 B conf
Designing, Analyzing and Exploiting Stake-Based Social Networks.
ASONAM
Tsung-Ting Kuo, Jung-Jung Yeh, Chih-Jen Lin, Shou-De Lin
2010 J jnl
Iterative Scaling and Coordinate Descent Methods for Maximum Entropy Models
J. Mach. Learn. Res.
Fang-Lan Huang, Cho-Jui Hsieh, Kai-Wei Chang, Chih-Jen Lin
2010 A* conf
Large linear classification when data cannot fit in memory.
KDD
Hsiang-Fu Yu, Cho-Jui Hsieh, Kai-Wei Chang, Chih-Jen Lin
2010 J jnl
Training and Testing Low-degree Polynomial Data Mappings via Linear SVM.
J. Mach. Learn. Res.
Yin-Wen Chang, Cho-Jui Hsieh, Kai-Wei Chang, Michael Ringgaard, Chih-Jen Lin
2009 — conf
An Ensemble of Three Classifiers for KDD Cup 2009: Expanded Linear Model, Heterogeneous Boosting, and Selective Naive Bayes.
KDD Cup
Hung-Yi Lo, Kai-Wei Chang, Shang-Tse Chen, Tsung-Hsien Chiang, Chun-Sung Ferng, Cho-Jui Hsieh, Yi-Kuang Ko, Tsung-Ting Kuo, Hung-Che Lai, Ken-Yi Lin, Chia-Hsuan Wang, Hsiang-Fu Yu, Chih-Jen Lin, Hsuan-Tien Lin, Shou-De Lin
2009 — conf
Iterative Scaling and Coordinate Descent Methods for Maximum Entropy.
ACL/IJCNLP (2)
Fang-Lan Huang, Cho-Jui Hsieh, Kai-Wei Chang, Chih-Jen Lin
2008 A* conf
A dual coordinate descent method for large-scale linear SVM.
ICML
Cho-Jui Hsieh, Kai-Wei Chang, Chih-Jen Lin, S. Sathiya Keerthi, S. Sundararajan
2008 A* conf
A sequential dual method for large scale multi-class linear svms.
KDD
S. Sathiya Keerthi, S. Sundararajan, Kai-Wei Chang, Cho-Jui Hsieh, Chih-Jen Lin
2008 J jnl
Coordinate Descent Method for Large-scale L2-loss Linear Support Vector Machines.
J. Mach. Learn. Res.
Kai-Wei Chang, Cho-Jui Hsieh, Chih-Jen Lin
2008 J jnl
Cross-generation and cross-laboratory predictions of Affymetrix microarrays by rank-based methods.
J. Biomed. Informatics
Hsi-Che Liu, Chien-Yu Chen, Yu-Ting Liu, Cheng-Bang Chu, Der-Cherng Liang, Lee-Yung Shih, Chih-Jen Lin
2008 — conf
Feature Ranking Using Linear SVM.
WCCI Causation and Prediction Challenge
Yin-Wen Chang, Chih-Jen Lin
2008 J jnl
LIBLINEAR: A Library for Large Linear Classification.
J. Mach. Learn. Res.
Rong-En Fan, Kai-Wei Chang, Cho-Jui Hsieh, Xiang-Rui Wang, Chih-Jen Lin
2008 — conf
Parallel Spectral Clustering.
ECML/PKDD (2)
Yangqiu Song, WenYen Chen, Hongjie Bai, Chih-Jen Lin, Edward Y. Chang
2008 J jnl
Trust Region Newton Method for Logistic Regression.
J. Mach. Learn. Res.
Chih-Jen Lin, Ruby C. Weng, S. Sathiya Keerthi
2007 J jnl
A note on Platt's probabilistic outputs for support vector machines.
Mach. Learn.
Hsuan-Tien Lin, Chih-Jen Lin, Ruby C. Weng
2007 J jnl
On the Convergence of Multiplicative Update Algorithms for Nonnegative Matrix Factorization.
IEEE Trans. Neural Networks
Chih-Jen Lin
2007 J jnl
Projected Gradient Methods for Nonnegative Matrix Factorization.
Neural Comput.
Chih-Jen Lin
2007 — conf
The NTU Toolkit and Framework for High-Level Feature Detection at TRECVID 2007.
TRECVID
Ming-Fang Weng, Chun-Kang Chen, Yi-Hsuan Yang, Rong-En Fan, Yu-Ting Hsieh, Yung-Yu Chuang, Winston H. Hsu, Chih-Jen Lin
2007 A* conf
Trust region Newton methods for large-scale logistic regression.
ICML
Chih-Jen Lin, Ruby C. Weng, S. Sathiya Keerthi
2006 J jnl
A study on SMO-type decomposition methods for support vector machines.
IEEE Trans. Neural Networks
Pai-Hsuen Chen, Rong-En Fan, Chih-Jen Lin
2006 — ch.
Combining SVMs with Various Feature Selection Strategies.
Feature Extraction
Yi-Wei Chen, Chih-Jen Lin
2006 J jnl
Generalized Bradley-Terry Models and Multi-Class Probability Estimates.
J. Mach. Learn. Res.
Tzu-Kuo Huang, Ruby C. Weng, Chih-Jen Lin
2006 A* conf
Ranking individuals by group comparisons.
ICML
Tzu-Kuo Huang, Chih-Jen Lin, Ruby C. Weng
2005 J jnl
Leave-One-Out Bounds for Support Vector Regression Model Selection.
Neural Comput.
Ming-Wei Chang, Chih-Jen Lin
2005 B conf
Training Support Vector Machines via SMO-Type Decomposition Methods.
ALT
Pai-Hsuen Chen, Rong-En Fan, Chih-Jen Lin
2005 B conf
Training Support Vector Machines via SMO-Type Decomposition Methods.
Discovery Science
Pai-Hsuen Chen, Rong-En Fan, Chih-Jen Lin
2005 J jnl
Working Set Selection Using Second Order Information for Training Support Vector Machines.
J. Mach. Learn. Res.
Rong-En Fan, Pai-Hsuen Chen, Chih-Jen Lin
2004 — conf
A Generalized Bradley-Terry Model: From Group Competition to Individual Skill.
NIPS
Tzu-Kuo Huang, Chih-Jen Lin, Ruby C. Weng
2004 J jnl
Analysis of switching dynamics with competing support vector machines.
IEEE Trans. Neural Networks
Ming-Wei Chang, Chih-Jen Lin, Ruby Chiu-Hsing Weng
2004 J jnl
Decomposition Methods for Linear Support Vector Machines.
Neural Comput.
Wei-Chun Kao, Kai-Min Chung, Chia-Liang Sun, Chih-Jen Lin
2004 J jnl
Probability Estimates for Multi-class Classification by Pairwise Coupling.
J. Mach. Learn. Res.
Ting-Fan Wu, Chih-Jen Lin, Ruby C. Weng
2003 J jnl
A study on reduced support vector machines.
IEEE Trans. Neural Networks
Kuan-Ming Lin, Chih-Jen Lin
2003 J jnl
Asymptotic Behaviors of Support Vector Machines with Gaussian Kernel.
Neural Comput.
S. Sathiya Keerthi, Chih-Jen Lin
2003 — conf
Decomposition methods for linear support vector machines.
ICASSP (4)
Kai-Min Chung, Wei-Chun Kao, Tony Sun, Chih-Jen Lin
2003 — conf
Probability Estimates for Multi-Class Classification by Pairwise Coupling.
NIPS
Ting-Fan Wu, Chih-Jen Lin, Ruby C. Weng
2003 J jnl
Radius Margin Bounds for Support Vector Machines with the RBF Kernel.
Neural Comput.
Kai-Min Chung, Wei-Chun Kao, Chia-Liang Sun, Li-Lun Wang, Chih-Jen Lin
2003 J jnl
Special issue on support vector machines.
Neurocomputing
Colin Campbell, Chih-Jen Lin, S. Sathiya Keerthi, V. David Sánchez A.
2002 J jnl
A Note on the Decomposition Methods for Support Vector Regression.
Neural Comput.
Shuo-Peng Liao, Hsuan-Tien Lin, Chih-Jen Lin
2002 J jnl
A Simple Decomposition Method for Support Vector Machines.
Mach. Learn.
Chih-Wei Hsu, Chih-Jen Lin
2002 J jnl
A comparison of methods for multiclass support vector machines.
IEEE Trans. Neural Networks
Chih-Wei Hsu, Chih-Jen Lin
2002 J jnl
A formal analysis of stopping criteria of decomposition methods for support vector machines.
IEEE Trans. Neural Networks
Chih-Jen Lin
2002 — conf
Analysis of Nonstationary Time Series Using Support Vector Machines.
SVM
Ming-Wei Chang, Chih-Jen Lin, Ruby C. Weng
2002 J jnl
Asymptotic convergence of an SMO algorithm without any assumptions.
IEEE Trans. Neural Networks
Chih-Jen Lin
2002 J jnl
Errata to "A comparison of methods for multiclass support vector machines".
IEEE Trans. Neural Networks
Chih-Jen Lin
2002 J jnl
Errata to "On the convergence of the decomposition method for support vector machines".
IEEE Trans. Neural Networks
Chih-Jen Lin
2002 J jnl
Training
Neural Comput.
Chih-Chung Chang, Chih-Jen Lin
2001 J jnl
Formulations of Support Vector Machines: A Note from an Optimization Point of View.
Neural Comput.
Chih-Jen Lin
2001 J jnl
On the convergence of the decomposition method for support vector machines.
IEEE Trans. Neural Networks
Chih-Jen Lin
2001 J jnl
Optical Coating Designs Using the Family Competition Evolutionary Algorithm.
Evol. Comput.
Jinn-Moon Yang, Jorng-Tzong Horng, Chih-Jen Lin, Cheng-Yan Kao
2001 J jnl
Solving General Capacity Problem by Relaxed Cutting Plane Approach.
Ann. Oper. Res.
Soon-Yi Wu, Shu-Cherng Fang, Chih-Jen Lin
2001 J jnl
Training nu-Support Vector Classifiers: Theory and Algorithms.
Neural Comput.
Chih-Chung Chang, Chih-Jen Lin
2000 J jnl
The analysis of decomposition methods for support vector machines.
IEEE Trans. Neural Networks Learn. Syst.
Chih-Chung Chang, Chih-Wei Hsu, Chih-Jen Lin
1999 J jnl
Incomplete Cholesky Factorizations with Limited Memory.
SIAM J. Sci. Comput.
Chih-Jen Lin, Jorge J. Moré
1999 J jnl
Newton's Method for Large Bound-Constrained Optimization Problems.
SIAM J. Optim.
Chih-Jen Lin, Jorge J. Moré
1998 J jnl
An Unconstrained Convex Programming Approach to Linear Semi-Infinite Programming.
SIAM J. Optim.
Chih-Jen Lin, Shu-Cherng Fang, Soon-Yi Wu
1998 J jnl
Efficient test-point selection for scan-based BIST.
IEEE Trans. Very Large Scale Integr. Syst.
Huan-Chih Tsai, Kwang-Ting Cheng, Chih-Jen Lin, Sudipta Bhawmik
1997 A* conf
A Hybrid Algorithm for Test Point Selection for Scan-Based BIST.
DAC
Huan-Chih Tsai, Kwang-Ting Cheng, Chih-Jen Lin, Sudipta Bhawmik
1995 J jnl
Integration of partial scan and built-in self-test.
J. Electron. Test.
Chih-Jen Lin, Yervant Zorian, Sudipta Bhawmik
1995 A conf
Timing-Driven Test Point Insertion for Full-Scan and Partial-Scan BIST.
ITC
Kwang-Ting Cheng, Chih-Jen Lin
1993 A conf
Built-In Current Sensor for I
ITC
Ching-Wen Hsue, Chih-Jen Lin
1993 A conf
PSBIST: A Partial-Scan Based Built-In Self-Test Scheme.
ITC
Chih-Jen Lin, Yervant Zorian, Sudipta Bhawmik
1991 A* conf
Enhanced Controllability for
DAC
Tapan J. Chakraborty, Sudipta Bhawmik, Robert Bencivenga, Chih-Jen Lin