公開日期 | 標題 | 作者 | 來源出版物 | scopus | WOS | 全文 |
2015 | Subsampled Hessian Newton methods for supervised learning | CHIH-JEN LIN ; Wang, C.-C.; Huang, C.-C.; CHIH-JEN LIN | Neural Computation | | | |
2014 | Support vector machines | Wang, P.-W.; CHIH-JEN LIN | Data Classification: Algorithms and Applications | | | |
2004 | Support vector machines for data classification | Lin, Chih-Jen | | | | |
2004 | Support vector machines for data classification and regression | Lin, Chih-Jen | | | | |
2014 | Support Vector Machines. | Wang, Po-Wei; CHIH-JEN LIN | Data Classification: Algorithms and Applications | | | |
2008 | SVM 在結構資料上的應用 (新制多年期第1年) | 林智仁 | | | | |
2007 | SVM 在結構資料上的應用 (新制多年期第2年) | 林智仁 | | | | |
2000 | The analysis of decomposition methods for support vector machines | CHIH-JEN LIN ; Chang, Chih-Chung; Hsu, Chih-Wei; Lin, Chih-Jen; CHIH-JEN LIN | IEEE Transactions on Neural Networks | | | |
2007 | The NTU toolkit and framework for high-level feature detection at TRECVID 2007 | CHIH-JEN LIN ; Weng, M.-F.; Chen, C.-K.; Yang, Y.-H.; Fan, R.-E.; Hsieh, Y.-T.; Chunag, Y.-Y.; Hsu, W.H.; CHIH-JEN LIN | 2007 TREC Video Retrieval Evaluation Notebook Papers | | | |
1995 | Timing-Driven Test Point Insertion for Full-Scan and Partial-Scan BIST. | Cheng, Kwang-Ting; CHIH-JEN LIN | Proceedings IEEE International Test Conference 1995, Driving Down the Cost of Test, Washington, DC, USA, October 21-25, 1995 | | | |
2010 | Training and Testing Low-degree Polynomial Data Mappings via Linear SVM | Chang, Yin-Wen; Hsieh, Cho-Jui; Chang, Kai-Wei; Ringgaard, Michael; Lin, Chih-Jen | Journal of Machine Learning Research | | | |
2005 | Training Support Vector Machines via SMO-Type Decomposition Methods. | Chen, Pai-Hsuen; Fan, Rong-En; CHIH-JEN LIN | Algorithmic Learning Theory, 16th International Conference, ALT 2005, Singapore, October 8-11, 2005, Proceedings | | | |
2001 | Training v-Support Vector Classifiers: Theory and Algorithms | Chang, Chih-Chung; Lin, Chih-Jen | Neural Computation | | | |
2002 | Training v-support vector regression: Theory and algorithms | Chang, Chih-Chung; Lin, Chih-Jen | Neural Computation | 274 | 230 | |
2001 | Training ν-support vector classifiers: Theory and algorithms | CHIH-JEN LIN ; Chang, C.-C.; CHIH-JEN LIN | Neural Computation | | | |
2008 | Trust region Newton method for large-scale logistic regression | CHIH-JEN LIN ; Lin, C.-J.; Weng, R.C.; Sathiya Keerthi, S.; CHIH-JEN LIN | Journal of Machine Learning Research | | | |
2008 | Trust Region Newton Method for Logistic Regression | Lin, Chih-Jen ; Weng, Ruby C.; Keerthi, S. Sathiya | The Journal of Machine Learning Research | | | |
2007 | Trust region Newton methods for large-scale logistic regression. | Lin, Chih-Jen; Weng, Ruby C.; CHIH-JEN LIN | Machine Learning, Proceedings of the Twenty-Fourth International Conference (ICML 2007), Corvallis, Oregon, USA, June 20-24, 2007 | 87 | 0 | |
2005 | A Tutorial on $nu$-Support Vector Machines | Chen, Pai-Hsuen; Lin, Chih-Jen ; Scholkopf, Bernhard | Applied Stochastic Models in Business and Industry | | | |
2005 | A tutorial on v-support vector machines | Chen, P.-H.; Lin, C.-J.; Sch?lkopf, B.; CHIH-JEN LIN | Applied Stochastic Models in Business and Industry | | | |