公開日期 | 標題 | 作者 | 來源出版物 | scopus | WOS | 全文 |
1994 | On solving convex quadratic semi-infinite programming problems | Fang, Shu-Cherng; Lin, Chih-Jen ; Wu, Soon-Yi | Optimization | | | |
2006 | On the Convergence of Multiplicative Update
Algorithms for Non-negative Matrix Factorization | Lin, Chih-Jen | | | | |
2007 | On the convergence of multiplicative update algorithms for nonnegative matrix factorization | Lin, C.-J.; CHIH-JEN LIN | IEEE Transactions on Neural Networks | 312 | 274 | |
2001 | On the convergence of the decomposition method for support vector machines | Lin, C.-J.; CHIH-JEN LIN | IEEE Transactions on Neural Networks | 195 | 164 | |
2023 | On the Thresholding Strategy for Infrequent Labels in Multi-label Classification | YU-JEN LIN; CHIH-JEN LIN | International Conference on Information and Knowledge Management, Proceedings | 0 | | |
2022 | On the Use of Unrealistic Predictions in Hundreds of Papers Evaluating Graph Representations | Lin, Li Chung; Liu, Cheng Hung; Chen, Chih Ming; Hsu, Kai Chin; Wu, I. Feng; Tsai, Ming Feng; CHIH-JEN LIN | Proceedings of the 36th AAAI Conference on Artificial Intelligence, AAAI 2022 | 2 | | |
2001 | Optical coating design using the family competition evolutionaty algorithm | Yang, Jinn-Moon; Horng, Jorng-Tzong; Lin, Chih-Jen ; Kao, Cheng-Yan | Evolutionary Computation | | | |
2001 | Optical Coating Designs Using the Family Competition Evolutionary Algorithm. | Yang, Jinn-Moon; Horng, Jorng-Tzong; Lin, Chih-Jen; Kao, Cheng-Yan; CHIH-JEN LIN | Evolutionary Computation | 7 | 8 | |
2005 | Optimization, Support Vector Machines,
and Machine Learning | Lin, Chih-Jen | | | | |
2016 | Parallel Dual Coordinate Descent Method for Large-scale Linear Classification in Multi-core Environments. | Chiang, Wei-Lin; Lee, Mu-Chu; Lin, Chih-Jen; CHIH-JEN LIN | Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Francisco, CA, USA, August 13-17, 2016 | 31 | 0 | |
2008 | Parallel spectral clustering | Song, Y.; Chen, W.-Y.; Bai, H.; Lin, C.-J.; Chang, E.Y.; CHIH-JEN LIN | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | 56 | 0 | |
2011 | Parallel spectral clustering in distributed systems | Chen, W.-Y.; Song, Y.; Bai, H.; Lin, C.-J.; Chang, E.Y.; CHIH-JEN LIN | IEEE Transactions on Pattern Analysis and Machine Intelligence | 504 | 358 | |
2008 | Parallel Spectral Clustering. | Song, Yangqiu; Chen, WenYen; Bai, Hongjie; Lin, Chih-Jen; Chang, Edward Y.; CHIH-JEN LIN | Machine Learning and Knowledge Discovery in Databases, European Conference, ECML/PKDD 2008, Antwerp, Belgium, September 15-19, 2008, Proceedings, Part II | 56 | 0 | |
2020 | Parameter Selection for Linear Support Vector Regression | Hsia, J.; Lin, C.; CHIH-JEN LIN | IEEE Transactions on Neural Networks and Learning Systems | 20 | 15 | |
2021 | Parameter Selection: WhyWe Should Pay More Attention to It | Liu J.-J; Yang T.-H; Chen S.-A; Lin C.-J.; CHIH-JEN LIN | ACL-IJCNLP 2021 - 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, Proceedings of the Conference | 2 | | |
1996 | Parametric linear semi-infinite programming | Lin, C.-J.; Fang, S.-C.; Wu, S.-Y.; CHIH-JEN LIN | Applied Mathematics Letters | 2 | 1 | |
2022 | Practical Counterfactual Policy Learning for Top-K Recommendations | Liu, Yaxu; Yen, Jui Nan; Yuan, Bowen; Shi, Rundong; Yan, Peng; CHIH-JEN LIN | Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining | 5 | 0 | |
2003 | A practical guide to support vector classification | Hsu, Chih-Wei; Chang, Chih-Chung; Lin, Chih-Jen | | | | |
2003 | A practical guide to support vector classification | Lin, Chih-Jen | | | | |
2018 | Preconditioned Conjugate Gradient Methods in Truncated Newton Frameworks for Large-scale Linear Classification. | Hsia, Chih-Yang; Chiang, Wei-Lin; Lin, Chih-Jen; CHIH-JEN LIN | Proceedings of The 10th Asian Conference on Machine Learning, ACML 2018, Beijing, China, November 14-16, 2018. | | | |