| 2025 | CIKM | SparseKmeans: Efficient K-means Clustering For Sparse Data. | Khoi Nguyen Pham Dang, He-Zhe Lin, Chih-Jen Lin |
| 2025 | ICDM | Revisiting One-Versus-One and One-Versus-Rest: Insights into Imbalanced Multi-Class Classification. | Kuan-Ting Chen, Chih-Jen Lin |
| 2025 | NAACL | Preserving Zero-shot Capability in Supervised Fine-tuning for Multi-label Text Classification. | Si-An Chen, Hsuan-Tien Lin, Chih-Jen Lin |
| 2024 | EMNLP | Random Label Forests: An Ensemble Method with Label Subsampling For Extreme Multi-Label Problems. | Sheng-Wei Chen, Chih-Jen Lin |
| 2024 | EMNLP | Exploring Space Efficiency in a Tree-based Linear Model for Extreme Multi-label Classification. | He-Zhe Lin, Cheng-Hung Liu, Chih-Jen Lin |
| 2024 | RecSys | One-class Matrix Factorization: Point-Wise Regression-Based or Pair-Wise Ranking-Based? | Sheng-Wei Chen, Chih-Jen Lin |
| 2023 | ACL | Linear Classifier: An Often-Forgotten Baseline for Text Classification. | Yu-Chen Lin, Si-An Chen, Jie-Jyun Liu, Chih-Jen Lin |
| 2023 | CIKM | On the Thresholding Strategy for Infrequent Labels in Multi-label Classification. | Yu-Jen Lin, Chih-Jen Lin |
| 2023 | SIGIR | On the "Rough Use" of Machine Learning Techniques. | Chih-Jen Lin |
| 2022 | AAAI | 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 |
| 2022 | KDD | Practical Counterfactual Policy Learning for Top-K Recommendations. | Yaxu Liu, Jui-Nan Yen, Bo-Wen Yuan, Rundong Shi, Peng Yan, Chih-Jen Lin |
| 2022 | NAACL | Even the Simplest Baseline Needs Careful Re-investigation: A Case Study on XML-CNN. | Si-An Chen, Jie-Jyun Liu, Tsung-Han Yang, Hsuan-Tien Lin, Chih-Jen Lin |
| 2021 | ACL | Parameter Selection: Why We Should Pay More Attention to It. | Jie-Jyun Liu, Tsung-Han Yang, Si-An Chen, Chih-Jen Lin |
| 2021 | ICDM | Limited-memory Common-directions Method With Subsampled Newton Directions for Large-scale Linear Classification. | Jui-Nan Yen, Chih-Jen Lin |
| 2021 | KDD | Efficient Optimization Methods for Extreme Similarity Learning with Nonlinear Embeddings. | Bo-Wen Yuan, Yu-Sheng Li, Pengrui Quan, Chih-Jen Lin |
| 2020 | MDM | AutoConjunction: Adaptive Model-based Feature Conjunction for CTR Prediction. | Chih-Yao Chang, Xing Tang, Bo-Wen Yuan, Jui-Yang Hsia, Zhirong Liu, Zhenhua Dong, Xiuqiang He, Chih-Jen Lin |
| 2020 | RecSys | Unbiased Ad Click Prediction for Position-aware Advertising Systems. | Bo-Wen Yuan, Yaxu Liu, Jui-Yang Hsia, Zhenhua Dong, Chih-Jen Lin |
| 2020 | SDM | Two-variable Dual Coordinate Descent Methods for Linear SVM with/without the Bias Term. | Chi-Cheng Chiu, Pin-Yen Lin, Chih-Jen Lin |
| 2020 | SDM | Dual Coordinate-Descent Methods for Linear One-Class SVM and SVDD. | Hung-Yi Chou, Pin-Yen Lin, Chih-Jen Lin |
| 2019 | CIKM | Improving Ad Click Prediction by Considering Non-displayed Events. | Bo-Wen Yuan, Jui-Yang Hsia, Mengyuan Yang, Hong Zhu, Chih-Yao Chang, Zhenhua Dong, Chih-Jen Lin |
| 2018 | ACML | Preconditioned Conjugate Gradient Methods in Truncated Newton Frameworks for Large-scale Linear Classification. | Chih-Yang Hsia, Wei-Lin Chiang, Chih-Jen Lin |
| 2018 | CIKM | Naive Parallelization of Coordinate Descent Methods and an Application on Multi-core L1-regularized Classification. | Yong Zhuang, Yu-Chin Juan, Guo-Xun Yuan, Chih-Jen Lin |
| 2018 | SDM | Limited-memory Common-directions Method for Distributed Ll-regularized Linear Classification. | Wei-Lin Chiang, Yu-Sheng Li, Ching-Pei Lee, Chih-Jen Lin |
| 2017 | AAAI | A Unified Algorithm for One-Cass Structured Matrix Factorization with Side Information. | Hsiang-Fu Yu, Hsin-Yuan Huang, Inderjit S. Dhillon, Chih-Jen Lin |
| 2017 | ACML | A Study on Trust Region Update Rules in Newton Methods for Large-scale Linear Classification. | Chih-Yang Hsia, Ya Zhu, Chih-Jen Lin |
| 2017 | SDM | 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 |
| 2017 | SDM | Selection of Negative Samples for One-class Matrix Factorization. | Hsiang-Fu Yu, Mikhail Bilenko, Chih-Jen Lin |
| 2016 | KDD | Parallel Dual Coordinate Descent Method for Large-scale Linear Classification in Multi-core Environments. | Wei-Lin Chiang, Mu-Chu Lee, Chih-Jen Lin |
| 2016 | RecSys | Field-aware Factorization Machines for CTR Prediction. | Yu-Chin Juan, Yong Zhuang, Wei-Sheng Chin, Chih-Jen Lin |
| 2016 | SDM | Linear and Kernel Classification: When to Use Which? | Hsin-Yuan Huang, Chih-Jen Lin |
| 2015 | ICDM | Fast Matrix-Vector Multiplications for Large-Scale Logistic Regression on Shared-Memory Systems. | Mu-Chu Lee, Wei-Lin Chiang, Chih-Jen Lin |
| 2015 | KDD | Warm Start for Parameter Selection of Linear Classifiers. | Bo-Yu Chu, Chia-Hua Ho, Cheng-Hao Tsai, Chieh-Yen Lin, Chih-Jen Lin |
| 2015 | PAKDD | A Learning-Rate Schedule for Stochastic Gradient Methods to Matrix Factorization. | Wei-Sheng Chin, Yong Zhuang, Yu-Chin Juan, Chih-Jen Lin |
| 2015 | PAKDD | Distributed Newton Methods for Regularized Logistic Regression. | Yong Zhuang, Wei-Sheng Chin, Yu-Chin Juan, Chih-Jen Lin |
| 2014 | KDD | Incremental and decremental training for linear classification. | Cheng-Hao Tsai, Chieh-Yen Lin, Chih-Jen Lin |
| 2014 | SDM | Large-scale Kernel RankSVM. | Tzu-Ming Kuo, Ching-Pei Lee, Chih-Jen Lin |
| 2013 | CVPR | Dense Non-rigid Point-Matching Using Random Projections. | Raffay Hamid, Dennis DeCoste, Chih-Jen Lin |
| 2013 | CVPR | Large-Scale Video Summarization Using Web-Image Priors. | Aditya Khosla, Raffay Hamid, Chih-Jen Lin, Neel Sundaresan |
| 2013 | KDD | Effective string processing and matching for author disambiguation. | 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 | KDD | 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 |
| 2013 | RecSys | A fast parallel SGD for matrix factorization in shared memory systems. | Yong Zhuang, Wei-Sheng Chin, Yu-Chin Juan, Chih-Jen Lin |
| 2012 | KDD | Experiences and lessons in developing industry-strength machine learning and data mining software. | Chih-Jen Lin |
| 2011 | IJCAI | Large Linear Classification When Data Cannot Fit in Memory. | Hsiang-Fu Yu, Cho-Jui Hsieh, Kai-Wei Chang, Chih-Jen Lin |
| 2011 | KDD | An improved GLMNET for l1-regularized logistic regression. | Guo-Xun Yuan, Chia-Hua Ho, Chih-Jen Lin |
| 2010 | IJCNN | Active learning strategies using SVMs. | Ming-Hen Tsai, Chia-Hua Ho, Chih-Jen Lin |
| 2010 | KDD | Large linear classification when data cannot fit in memory. | Hsiang-Fu Yu, Cho-Jui Hsieh, Kai-Wei Chang, Chih-Jen Lin |
| 2009 | ACL | Iterative Scaling and Coordinate Descent Methods for Maximum Entropy. | Fang-Lan Huang, Cho-Jui Hsieh, Kai-Wei Chang, Chih-Jen Lin |
| 2008 | ICML | A dual coordinate descent method for large-scale linear SVM. | Cho-Jui Hsieh, Kai-Wei Chang, Chih-Jen Lin, S. Sathiya Keerthi, S. Sundararajan |
| 2008 | KDD | A sequential dual method for large scale multi-class linear svms. | S. Sathiya Keerthi, S. Sundararajan, Kai-Wei Chang, Cho-Jui Hsieh, Chih-Jen Lin |
| 2007 | ICML | Trust region Newton methods for large-scale logistic regression. | Chih-Jen Lin, Ruby C. Weng, S. Sathiya Keerthi |
| 2006 | ICML | Ranking individuals by group comparisons. | Tzu-Kuo Huang, Chih-Jen Lin, Ruby C. Weng |
| 2005 | ALT | Training Support Vector Machines via SMO-Type Decomposition Methods. | Pai-Hsuen Chen, Rong-En Fan, Chih-Jen Lin |
| 2005 | DIS | Training Support Vector Machines via SMO-Type Decomposition Methods. | Pai-Hsuen Chen, Rong-En Fan, Chih-Jen Lin |
| 2003 | ICASSP | Decomposition methods for linear support vector machines. | Kai-Min Chung, Wei-Chun Kao, Tony Sun, Chih-Jen Lin |
| 1997 | DAC | A Hybrid Algorithm for Test Point Selection for Scan-Based BIST. | Huan-Chih Tsai, Kwang-Ting Cheng, Chih-Jen Lin, Sudipta Bhawmik |
| 1995 | ITC | Timing-Driven Test Point Insertion for Full-Scan and Partial-Scan BIST. | Kwang-Ting Cheng, Chih-Jen Lin |
| 1993 | ITC | Built-In Current Sensor for I | Ching-Wen Hsue, Chih-Jen Lin |
| 1993 | ITC | PSBIST: A Partial-Scan Based Built-In Self-Test Scheme. | Chih-Jen Lin, Yervant Zorian, Sudipta Bhawmik |
| 1991 | DAC | Enhanced Controllability for | Tapan J. Chakraborty, Sudipta Bhawmik, Robert Bencivenga, Chih-Jen Lin |