Chih-Jen Lin
Affiliated Professor of Machine Learning
Research interests
Lin's main research interests are the development of machine learning algorithms and software. He bridged optimization techniques and machine learning algorithms. He pioneered the construction of open-source machine learning packages and has focused a lot on the practical realization of machine learning methodology. Email
Lin is currently a distinguished professor at the Department of Computer Science, National Taiwan University. He obtained his bachelor degree from National Taiwan University, Taiwan in 1993 and Ph.D. degree from University of Michigan, USA in 1998.
His major research areas include machine learning, data mining, and numerical optimization. He is best known for his work on support vector machines (SVM) for data classification. He and his team developed widely used machine learning packages including LIBSVM (a library for support vector machines) and LIBLINEAR (a library for large linear classification).
He has received many awards for his research work, including best paper awards in some top computer science conferences. He is a fellow of the Association of Advancement of Artificial Intelligence (AAAI), the Institute of Electrical and Electronics Engineers (IEEE), and the Association for Computing Machinery (ACM) for his contribution to machine learning algorithms and software design.
- Ph.D. in industrial and operations engineering from University of Michigan, USA
- Master’s in industrial and operations engineering from University of Michigan, USA
- Bachelor in mathematics from National Taiwain University, Taiwan
- Fellow, Association for Computing Machinery (ACM), 2015
- Fellow, Association of Advancement of Artificial Intelligence (AAAI), 2014
- Fellow, Institute of Electrical and Electronics Engineers (IEEE), 2011
- Distinguished Scientist, Association for Computing Machinery (ACM), 2011
- Best paper award, ACML (Asian Conference on Machine Learning) 2018 (with two students)
- Best paper award, ACM Recommender Systems 2013 (with three students)
- Best paper award, ACM KDD 2010 (with three students)
Lin has been a leading researcher in the field of machine learning algorithms and software design. His contributions to bridge optimization and machine learning include the creation of effective algorithms for support vector machines (SVM) and large-scale linear classification.
- Li-ChungLin, Cheng-Hung Liu, Chih-Ming Chen, Kai-Chin Hsu, I-Feng Wu, Ming-Feng Tsai, and Chih-Jen On the use of unrealistic predictions in hundreds of papers evaluating graph representations. In Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI), 2022.
- Bowen Yuan, Yu-Sheng Li, Pengrui Quan, andChih-Jen Efficient optimization methods for extreme similarity learning with nonlinear embeddings. In Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2021.
- Yuchin Juan, Yong Zhuang, Wei-Sheng Chin, andChih-Jen Field-aware factorization machines for CTR prediction. In Proceedings of the ACM Recommender Systems Conference (RecSys), 2016.
- Chih-Chung Chang andChih-Jen LIBSVM: a library for support vector machines. ACM Transactions on Intelligent Systems and Technology, 2(3):27:1-27:27, 2011.
- Rong-En Fan, Kai-Wei Chang, Cho-Jui Hsieh, Xiang-Rui Wang, andChih-Jen LIBLINEAR: a library for large linear classification. Journal of Machine Learning Research, 9:1871-1874, 2008.
- Chih-Wei Hsu andChih-Jen A comparison of methods for multi-class support vector machines. IEEE Transactions on Neural Networks, 13(2):415-425, 2002.
Related
Lin provides critical insights at SIGIR 2023
MBZUAI affiliated professor of Machine Learning Chih-Jen Lin gave one of the keynotes at the recent 46th International ACM SIGIR…
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