| Issue Date | Title | Author(s) | Source | scopus | WOS | Fulltext/Archive link |
| 2011 | A Bayesian approximation method for online ranking | Weng, R.C.; Lin, C.-J.; CHIH-JEN LIN | Journal of Machine Learning Research | | | |
| 2010 | A comparison of optimization methods and software for large-scale L1-regularized linear classification | Yuan, G.-X.; Chang, K.W.; Hsieh, C.-J.; Lin, C.-J.; CHIH-JEN LIN | Journal of Machine Learning Research | | | |
| 2008 | A dual coordinate descent method for large-scale linear SVM | Hsieh, C.-J.; Chang, K.-W.; Lin, C.-J.; Keerthi, S.S.; Sundararajan, S.; CHIH-JEN LIN | 25th International Conference on Machine Learning | | | |
| 2013 | A fast parallel SGD for matrix factorization in shared memory systems | Zhuang, Y.; Chin, W.-S.; Juan, Y.-C.; Lin, C.-J.; CHIH-JEN LIN | 7th ACM Conference on Recommender Systems | | | |
| 2015 | A fast parallel stochastic gradient method for matrix factorization in shared memory systems | Chin, W.-S.; Zhuang, Y.; Juan, Y.-C.; Lin, C.-J.; CHIH-JEN LIN | ACM Transactions on Intelligent Systems and Technology | | | |
| 2002 | A formal analysis of stopping criteria of decomposition methods for support vector machines | Lin, Chih-Jen; CHIH-JEN LIN | IEEE Transactions on Neural Networks | | |  |
| 2005 | A generalized bradley-terry model: From group competition to individual skill | Huang, T.-K.; Lin, C.-J.; Weng, R.C.; CHIH-JEN LIN | Advances in Neural Information Processing Systems | | | |
| 2015 | A learning-rate schedule for stochastic gradient methods to matrix factorization | Chin, W.-S.; Zhuang, Y.; Juan, Y.-C.; Lin, C.-J.; CHIH-JEN LIN | Lecture Notes in Computer Science | | | |
| 2002 | A note on the decomposition methods for support vector regression | Liao, Shuo-Peng; Lin, Hsuan-Tien; Lin, Chih-JenLiao, S.-P.; Lin, H.-T.; Lin, C.-J.; HSUAN-TIEN LIN ; CHIH-JEN LIN | Neural Computation | | | |
| 2008 | A sequential dual method for large scale multi-class linear svms | Keerthi, S.S.; Sundararajan, S.; Chang, K.-W.; Hsieh, C.-J.; Lin, C.-J.; CHIH-JEN LIN | ACM SIGKDD International Conference on Knowledge Discovery and Data Mining | | | |
| 2003 | A study of reduced support vector machines | Lin, Kuan-Min; Lin, Chih-Jen; CHIH-JEN LIN | IEEE Transactions on Neural Networks | | | |
| 2013 | A study on L2-loss (Squared Hinge-Loss) multiclass SVM | Lee, C.-P.; Lin, C.-J.; CHIH-JEN LIN | Neural Computation | | | |
| 2006 | A study on SMO-type decomposition methods for support vector machines | Chen, Pai-Hsuen; Fan, Rong-En; Lin, Chih-Jen; CHIH-JEN LIN | IEEE Transactions on Neural Networks | | | |
| 2010 | Active learning strategies using SVMs | Tsai, M.-H.; Ho, C.-H.; Lin, C.-J.; CHIH-JEN LIN | International Joint Conference on Neural Networks | | | |
| 2010 | Active learning strategies using SVMs. | Tsai, Ming-Hen; Ho, Chia-Hua; Lin, Chih-Jen; CHIH-JEN LIN | International Joint Conference on Neural Networks, IJCNN 2010, Barcelona, Spain, 18-23 July, 2010 | | | |
| 2002 | Adaptive deterministic annealing for two applications: competing SVR of switching dynamics and travelling salesman problems | Chang, Ming-Wei; Lin, Chih-Jen ; Weng, Ruby C. | 9th International Conference on Neural Information Processing | | | |
| 2002 | Adaptive deterministic annealing for two applications: Competing SVR of switching dynamics and travelling salesman problems | Chang, M.-W.; Lin, C.-J.; Weng, R.C.; CHIH-JEN LIN | ICONIP 2002 - Proceedings of the 9th International Conference on Neural Information Processing: Computational Intelligence for the E-Age | | | |
| 2012 | An improved GLMNET for l1-regularized logistic regression | Yuan, G.-X.; Ho, C.-H.; Lin, C.J.; CHIH-JEN LIN | Journal of Machine Learning Research | | | |
| 2011 | An improved glmnet for L1-regularized logistic regression | Yuan, G.-X.; Ho, C.-H.; Lin, C.-J.; CHIH-JEN LIN | ACM SIGKDD International Conference on Knowledge Discovery and Data Mining | | | |
| 1998 | An unconstrained convex programming approach to linear semi-infinite programming | Lin, C.-J.; Fang, S.-C.; Wu, S.-Y.; CHIH-JEN LIN | SIAM Journal on Optimization | | | |
