Hsuan-Tien Lin > Publications

Hsuan-Tien Lin

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2012

Yin-Hsi Kuo, Wen-Huang Cheng, Hsuan-Tien Lin and Winston H. Hsu. Unsupervised Semantic Feature Discovery for Image Object Retrieval and Tag Refinement. IEEE Transactions on Multimedia, to appear. Some preliminary parts appeared in CVPR '11.
Hsuan-Tien Lin and Ling Li. Reduction from Cost-sensitive Ordinal Ranking to Weighted Binary Classification. Neural Computation, to appear. Some preliminary parts appeared in NIPS '06 and PL Workshop @ ECML/PKDD '09.

2011

Chun-Sung Ferng and Hsuan-Tien Lin. Multi-label Classification with Error-correcting Codes. In Proceedings of ACML '11 (JMLR W&CP 20), , 281-295, 2011.
Chen-Wei Hung and Hsuan-Tien Lin. Multi-label Active Learning with Auxiliary Learner. In Proceedings of ACML '11 (JMLR W&CP 20), 315-332, 2011.
Te-Kang Jan, Hsuan-Tien Lin, Hsin-Pai Chen, Tsung-Chen Chern, Chung-Yueh Huang, Bing-Cheng Wen, Chia-Wen Chung, Yung-Jui Li, Ya-Ching Chuang, Li-Li Li, Yu-Jiun Chan, Juen-Kai Wang, Yuh-Lin Wang, Chi-Hung Lin and Da-Wei Wang. Cost-Sensitive Classification on Pathogen Species of Bacterial Meningitis by Surface Enhanced Raman Scattering. In Proceedings of BIBM '11, 2011.
Todd G. McKenzie, Chun-Sung Ferng, Yao-Nan Chen, Chun-Liang Li, Cheng-Hao Tsai, Kuan-Wei Wu, Ya-Hsuan Chang, Chung-Yi Li, Wei-Shih Lin, Shu-Hao Yu, Chieh-Yen Lin, Po-Wei Wang, Chia-Mau Ni, Wei-Lun Su, Tsung-Ting Kuo, Chen-Tse Tsai, Po-Lung Chen, Rong-Bing Chiu, Ku-Chun Chou, Yu-Cheng Chou, Chien-Chih Wang, Chen-Hung Wu, Hsuan-Tien Lin, Chih-Jen Lin and Shou-De Lin. Novel Models and Ensemble Techniques to Discriminate Favorite Items from Unrated Ones for Personalized Music Recommendation. National Taiwan University, August 2011; presented in the KDDCup 2011 Workshop. (First Prize of Track 2).
Po-Lung Chen, Chen-Tse Tsai, Yao-Nan Chen, Ku-Chun Chou, Chun-Liang Li, Cheng-Hao Tsai, Kuan-Wei Wu, Yu-Cheng Chou, Chung-Yi Li, Wei-Shih Lin, Shu-Hao Yu, Rong-Bing Chiu, Chieh-Yen Lin, Chien-Chih Wang, Po-Wei Wang, Wei-Lun Su, Chen-Hung Wu, Tsung-Ting Kuo, Todd G. McKenzie, Ya-Hsuan Chang, Chun-Sung Ferng, Chia-Mau Ni, Hsuan-Tien Lin, Chih-Jen Lin and Shou-De Lin. A Linear Ensemble of Individual and Blended Models for Music Rating Prediction. National Taiwan University, August 2011; presented in the KDDCup 2011 Workshop. (First Prize of Track 1).
Yin-Hsi Kuo, Hsuan-Tien Lin, Wen-Huang Cheng, Yi-Hsuan Yang and Winston H. Hsu. Unsupervised Auxiliary Visual Words Discovery for Large-Scale Image Object Retrieval. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), 905-912, 2011.

2010

Hsuan-Tien Lin. A Simple Cost-sensitive Multiclass Classification Algorithm Using One-versus-one Comparisons, National Taiwan University, December 2010; submitted.
Hsuan-Tien Lin. Cost-sensitive Classification: Status and Beyond. Workshop on Machine Learning Research in Taiwan: Challenges and Directions @ TAAI, 2010.
Farbound Tai and Hsuan-Tien Lin. Multi-label Classification with Principle Label Space Transformation. National Taiwan University, September 2010; submitted. A preliminary version appeared in MLD Workshop @ ICML '10.
Ming-Feng Tsai, Shang-Tse Chen, Yao-Nan Chen, Chun-Sung Ferng, Chia-Hsuan Wang, Tzay-Yeu Wen and Hsuan-Tien Lin. An Ensemble Ranking Solution to the Yahoo! Learning to Rank Challenge. National Taiwan University, Technical Report, September 2010.
Hsiang-Fu Yu, Hung-Yi Lo, Hsun-Ping Hsieh, Jing-Kai Lou, Todd G. McKenzie, Jung-Wei Chou, Po-Han Chung, Chia-Hua Ho, Chun-Fu Chang, Yin-Hsuan Wei, Jui-Yu Weng, En-Syu Yan, Che-Wei Chang, Tsung-Ting Kuo, Yi-Chen Lo, Po Tzu Chang, Chieh Po, Chien-Yuan Wang, Yi-Hung Huang, Chen-Wei Hung, Yu-Xun Ruan, Yu-Shi Lin, Shou-de Lin, Hsuan-Tien Lin and Chih-Jen Lin. Feature Engineering and Classifier Ensemble for KDD Cup 2010. National Taiwan University, June 2010; submitted. (First Prizes of Both All Teams and All Student Teams).
Farbound Tai and Hsuan-Tien Lin. Multi-label Classification with Principle Label Space Transformation. Second International Workshop on learning from Multi-Label Data @ ICML '10, 2010.
Han-Hsing Tu and Hsuan-Tien Lin. One-sided Support Vector Regression for Multiclass Cost-sensitive Classification. In Proceedings of ICML '10, 1095-1102, 2010.

2009

Hung-Yi Lo, Kai-Wei Chang, Shang-Tse Chen, Tsung-Hsien Chiang, Chun-Sung Ferng, Cho-Jui Hsieh, Yi-Kuang Ko, Tsung-Ting Kuo, Hung-Che Lai, Ken-Yi Lin, Chia-Hsuan Wang, Hsiang-Fu Yu, Chih-Jen Lin, Hsuan-Tien Lin and Shou-de Lin. An Ensemble of Three Classifiers for KDD Cup 2009: Expanded Linear Model, Heterogeneous Boosting, and Selective Naïve Bayes. In G. Dror et al., eds., Proceedings of KDD-Cup 2009 competition, vol. 7 of JMLR Workshop and Conference Proceedings, 57-64, 2009. (Third Place of the Slow Track).
Hsuan-Tien Lin and Ling Li. Combining Ordinal Preferences by Boosting. Preference Learning Workshop @ ECML/PKDD '09, 2009.

2008

Hsuan-Tien Lin. From Ordinal Ranking to Binary Classification. Ph.D. Dissertation, California Institute of Technology, May 2008; (Caltech ETD), (Local PDF)
Hsuan-Tien Lin and Ling Li. Support Vector Machinery for Infinite Ensemble Learning. Journal of Machine Learning Research, 9(2), 285-312, 2008; (Official Version). Some preliminary parts of the paper appeared in ECML '05 and ICONIP '05.

2007

Ling Li and Hsuan-Tien Lin. Optimizing 0/1 Loss for Perceptrons by Random Coordinate Descent. In Proceedings of IJCNN '07, 749-754, IEEE, 2007.
Hsuan-Tien Lin, Chih-Jen Lin, and Ruby C. Weng. A Note on Platt's Probabilistic Outputs for Support Vector Machines. Machine Learning, 68(3), 267-276, 2007; (Official Version).
Ling Li and Hsuan-Tien Lin. Ordinal Regression by Extended Binary Classification. In B. Schölkopf et al., eds., Advances in Neural Information Processing Systems: Proceedings of the 2006 Conference (NIPS '06), 865-872, MIT Press, 2007.

2006

Hsuan-Tien Lin and Ling Li. Large-Margin Thresholded Ensembles for Ordinal Regression: Theory and Practice. In J. Balcazár et al., eds., Algorithmic Learning Theory: ALT '06, vol. 4264 of Lecture Notes in Artificial Intelligence, 319-333, Springer-Verlag, 2006.

2005

Hsuan-Tien Lin and Ling Li. Novel Distance-Based SVM Kernels for Infinite Ensemble Learning. In Proceedings of ICONIP '05, 761-766, 2005.
Hsuan-Tien Lin and Ling Li. Infinite Ensemble Learning with Support Vector Machines. In J. Gama et al., eds., Machine Learning: ECML '05, vol. 3720 of Lecture Notes in Artificial Intelligence, 242-254, Springer-Verlag, 2005.
Hsuan-Tien Lin and Ling Li. Analysis of SAGE Results with Combined Learning Techniques. In P. Berka and B. Crémilleux, eds., Proceedings of the ECML/PKDD 2005 Discovery Challenge, 102-113, 2005.
Ling Li, Amrit Pratap, Hsuan-Tien Lin and Yaser S. Abu-Mostafa. Improving Generalization by Data Categorization. In A. Jorge et al., eds., Knowledge Discovery in Databases: PKDD '05, vol. 3721 of Lecture Notes in Artificial Intelligence, 157-168, Springer-Verlag, 2005.
Hsuan-Tien Lin. Infinite Ensemble Learning with Support Vector Machines. Master's Thesis, California Institute of Technology, May 2005; (Caltech ETD), (Updated PDF).

Before 2004

Hsuan-Tien Lin and Chih-Jen Lin. A Study on Sigmoid Kernels for SVM and the Training of non-PSD Kernels by SMO-type Methods. National Taiwan University, Technical Report, March 2003.
Shuo-Peng Liao, Hsuan-Tien Lin, and Chih-Jen Lin. A Note on the Decomposition Methods for Support Vector Regression. Neural Computation, 14(6), 1267-1281, 2002; (Official Version). A shorter version appeared in IJCNN '01.
Shuo-Peng Liao, Hsuan-Tien Lin, and Chih-Jen Lin. A Note on the Decomposition Methods for Support Vector Regression. In Proceedings of IJCNN '01, 1474-1479, IEEE/Omnipress, 2001.

Last updated at CST 06:28, January 03, 2012
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