Hsuan-Tien Lin

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2018

[CH2018] Cheng-Yu Hsieh, Yi-An Lin, and Hsuan-Tien Lin. A deep model with local surrogate loss for general cost-sensitive multi-label learning. In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), February 2018. [ bib | pdf ]

2017

[KL2017] Kuo-Hsuan Lo and Hsuan-Tien Lin. Cost-sensitive encoding for label space dimension reduction algorithms on multi-label classification. In Proceedings of the Conference on Technologies and Applications for Artificial Intelligence (TAAI), December 2017. [ bib | pdf ]
[HC2017] Hong-Min Chu, Kuan-Hao Huang, and Hsuan-Tien Lin. Dynamic principal projection for cost-sensitive online multi-label classification. Technical report, National Taiwan University, November 2017. [ bib | arxiv ]
[TJ2017] Te-Kang Jan, Da-Wei Wang, Chi-Hung Lin, and Hsuan-Tien Lin. Soft methodology for cost-and-error sensitive classification. Technical report, National Taiwan University and Academia Sinica, October 2017. A shorter version appeared in KDD '12. [ bib | arxiv | pdf ]
[YL2017] Yi-An Lin and Hsuan-Tien Lin. Cyclic classifier chain for cost-sensitive multilabel classification. In Proceedings of the IEEE International Conference on Data Science and Advanced Analytics (DSAA), October 2017. [ bib | pdf ]
[YY2017] Yao-Yuan Yang, Shao-Chuan Lee, Yu-An Chung, Tung-En Wu, Si-An Chen, and Hsuan-Tien Lin. libact: Pool-based active learning in python. Technical report, National Taiwan University, October 2017. [ bib | software | arxiv | pdf ]
[KH2017] Kuan-Hao Huang and Hsuan-Tien Lin. Cost-sensitive label embedding for multi-label classification. Machine Learning, 106(9--10):1725--1746, October 2017. Also presented in the journal track of ECML '17. [ bib | arxiv | pdf ]
[WS2017] Wei-Yuan Shen and Hsuan-Tien Lin. Active sampling of pairs and points for large-scale linear bipartite ranking. Technical report, National Taiwan University, August 2017. A shorter version appeared in ACML '13. [ bib | arxiv | pdf ]
[YW2017] Yu-Ping Wu and Hsuan-Tien Lin. Progressive k-labelsets for cost-sensitive multi-label classification. Machine Learning, 106(5):671--694, May 2017. Also presented in the journal track of ACML '16. [ bib | pdf ]

2016

[HC2016] Hong-Min Chu and Hsuan-Tien Lin. Can active learning experience be transferred? In Proceedings of the IEEE International Conference on Data Mining (ICDM), pages 841--846, December 2016. [ bib | arxiv | pdf ]
[KH2016b] Kuan-Hao Huang and Hsuan-Tien Lin. A novel uncertainty sampling algorithm for cost-sensitive multiclass active learning. In Proceedings of the IEEE International Conference on Data Mining (ICDM), pages 925--930, December 2016. [ bib | pdf ]
[CY2016] Chih-Kuan Yeh and Hsuan-Tien Lin. Automatic bridge bidding using deep reinforcement learning. In Proceedings of the 22nd European Conference on Artificial Intelligence (ECAI), pages 1362--1369, September 2016. [ bib | arxiv | pdf ]
[YC2016] Yu-An Chung, Hsuan-Tien Lin, and Shao-Wen Yang. Cost-aware pre-training for multiclass cost-sensitive deep learning. In Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI), pages 1411--1417, July 2016. [ bib | arxiv | pdf ]
[CL2016] Chun-Liang Li, Hsuan-Tien Lin, and Chi-Jen Lu. Rivalry of two families of algorithms for memory-restricted streaming pca. In Proceedings of the 19th International Conference on Artificial Intelligence and Statistics (AISTATS), pages 473--481, June 2016. [ bib | arxiv | pdf | appendix ]
[KH2016a] Kuan-Hao Huang and Hsuan-Tien Lin. Linear upper confidence bound algorithm for contextual bandit problem with piled rewards. In Proceedings of the Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), volume 1, pages 143--155, April 2016. [ bib | pdf ]
[SY2016] Sheng-Chi You and Hsuan-Tien Lin. A simple unlearning framework for online learning under concept drifts. In Proceedings of the Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), volume 1, pages 115--126, April 2016. [ bib | pdf ]

2015

[HY2015] Han-Jay Yang and Hsuan-Tien Lin. A practical divide-and-conquer approach for preference-based learning to rank. In Proceedings of the Conference on Technologies and Applications for Artificial Intelligence (TAAI), pages 554--561, October 2015. Winner of best paper award. [ bib | pdf ]
[CL2015b] Chun-Liang Li, Chun-Sung Ferng, and Hsuan-Tien Lin. Active learning using hint information. Neural Computation, 27(8):1738--1765, August 2015. A shorter version appeared in ACML '12. [ bib | pdf ]
[CL2015a] Chun-Liang Li, Yu-Chuan Su, Ting-Wei Lin, Cheng-Hao Tsai, Wei-Cheng Chang, Kuan-Hao Huang, Tzu-Ming Kuo, Shan-Wei Lin, Young-San Lin, Yu-Chen Lu, Chun-Pai Yang, Cheng-Xia Chang, Wei-Sheng Chin, Yu-Chin Juan, Hsiao-Yu Tung, Jui-Pin Wang, Cheng-Kuang Wei, Felix Wu, Tu-Chun Yin, Tong Yu, Yong Zhuang, Shou-De Lin, Hsuan-Tien Lin, and Chih-Jen Lin. Combination of feature engineering and ranking models for paper-author identification in KDD Cup 2013. Journal of Machine Learning Research, 16(12):2921--2947, December 2015. Extended first-place winner report of KDD Cup 2013 track 1. [ bib | pdf ]
[CH2015] Chun-Yen Ho and Hsuan-Tien Lin. Contract bridge bidding by learning. In Proceedings of the Workshop on Computer Poker and Imperfect Information @ AAAI, pages 30--36, January 2015. [ bib | pdf ]
[WH2015] Wei-Ning Hsu and Hsuan-Tien Lin. Active learning by learning. In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), pages 2659--2665, January 2015. [ bib | pdf ]

2014

[KC2014] Ku-Chun Chou, Chao-Kai Chiang, Hsuan-Tien Lin, and Chi-Jen Lu. Pseudo-reward algorithms for contextual bandits with linear payoff functions. In Proceedings of the Asian Conference on Machine Learning (ACML), volume 39 of JMLR Workshop and Conference Proceedings, pages 344--359, November 2014. [ bib | pdf ]
[HL2014] Hsuan-Tien Lin. Reduction from cost-sensitive multiclass classification to one-versus-one binary classification. In Proceedings of the Asian Conference on Machine Learning (ACML), volume 39 of JMLR Workshop and Conference Proceedings, pages 371--386, November 2014. [ bib | pdf ]
[WC2014] Wei-Sheng Chin, Yu-Chin Juan, Yong Zhuang, Felix Wu, Hsiao-Yu Tung, Tong Yu, Jui-Pin Wang, Cheng-Xia Chang, Chun-Pai Yang, Wei-Cheng Chang, Kuan-Hao Huang, Tzu-Ming Kuo, Shan-Wei Lin, Young-San Lin, Yu-Chen Lu, Yu-Chuan Su, Cheng-Kuang Wei, Tu-Chun Yin, Chun-Liang Li, Ting-Wei Lin, Cheng-Hao Tsai, Shou-De Lin, Hsuan-Tien Lin, and Chih-Jen Lin. Effective string processing and matching for author disambiguation. Journal of Machine Learning Research, 15(10):3037--3064, October 2014. Extended first-place winner report of KDD Cup 2013 track 2. [ bib | pdf ]
[CL2014b] Chun-Liang Li and Hsuan-Tien Lin. Condensed filter tree for cost-sensitive multi-label classification. In Proceedings of the International Conference on Machine Learning (ICML), pages 423--431, June 2014. [ bib | pdf | appendix ]
[SC2014] Shang-Tse Chen, Hsuan-Tien Lin, and Chi-Jen Lu. Boosting with online binary learners for the multiclass bandit problem. In Proceedings of the International Conference on Machine Learning (ICML), pages 342--350, June 2014. [ bib | pdf ]
[YC2014] Yu-Cheng Chou and Hsuan-Tien Lin. Machine learning approaches for interactive verification. In Proceedings of the Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), Part II, volume 8444 of Lecture Notes in Computer Science, pages 122--133, May 2014. [ bib | pdf ]
[YR2014] Yu-Xun Ruan, Hsuan-Tien Lin, and Ming-Feng Tsai. Improving ranking performance with cost-sensitive ordinal classification via regression. Information Retrieval, 17(1):1--20, February 2014. [ bib | pdf ]

2013

[KL2013] Ken-Yi Lin, Te-Kang Jan, and Hsuan-Tien Lin. Data selection techniques for large-scale RankSVM. In Proceedings of the Conference on Technologies and Applications for Artificial Intelligence (TAAI), pages 25--30, December 2013. [ bib | pdf ]
[YC2013] Ya-Hsuan Chang and Hsuan-Tien Lin. Pairwise regression with upper confidence bound for contextual bandit with multiple actions. In Proceedings of the Conference on Technologies and Applications for Artificial Intelligence (TAAI), pages 19--24, December 2013. [ bib | pdf ]
[PC2013] Po-Lung Chen and Hsuan-Tien Lin. Active learning for multiclass cost-sensitive classification using probabilistic models. In Proceedings of the Conference on Technologies and Applications for Artificial Intelligence (TAAI), pages 13--18, December 2013. [ bib | pdf ]
[WS2013] Wei-Yuan Shen and Hsuan-Tien Lin. Active sampling of pairs and points for large-scale linear bipartite ranking. In Proceedings of the Asian Conference on Machine Learning (ACML), volume 29 of JMLR Workshop and Conference Proceedings, pages 388--403, November 2013. [ bib | pdf ]
[CF2013] Chun-Sung Ferng and Hsuan-Tien Lin. Multilabel classification using error-correcting codes of hard or soft bits. IEEE Transactions on Neural Networks and Learning Systems, 24(11):1888--1900, November 2013. A shorter version appeared in ACML '11. [ bib | pdf ]

2012

[YC2012] Yao-Nan Chen and Hsuan-Tien Lin. Feature-aware label space dimension reduction for multi-label classification. In Advances in Neural Information Processing Systems: Proceedings of the 2012 Conference (NIPS), pages 1529--1537, December 2012. [ bib | pdf ]
[CL2012] Chun-Liang Li, Chun-Sung Ferng, and Hsuan-Tien Lin. Active learning with hinted support vector machine. In Proceedings of the Asian Conference on Machine Learning (ACML), volume 25 of JMLR Workshop and Conference Proceedings, pages 221--235, November 2012. [ bib | pdf ]
[FT2012] Farbound Tai and Hsuan-Tien Lin. Multilabel classification with principal label space transformation. Neural Computation, 24(9):2508--2542, September 2012. A preliminary version (under a mis-spelled title) appeared in the MLD Workshop @ ICML '10. [ bib | pdf ]
[YK2012] 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, 14(4):1079--1090, August 2012. [ bib | pdf ]
[TJ2012] Te-Kang Jan, Da-Wei Wang, Chi-Hung Lin, and Hsuan-Tien Lin. A simple methodology of soft cost-sensitive classification. In Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), pages 141--149, August 2012. [ bib | pdf ]
[KW2012] Kuan-Wei Wu, Chun-Sung Ferng, Chia-Hua Ho, An-Chun Liang, Chun-Heng Huang, Wei-Yuan Shen, Jyun-Yu Jiang, Ming-Hao Yang, Ting-Wei Lin, Ching-Pei Lee, Perng-Hwa Kung, Chin-En Wang, Ting-Wei Ku, Chun-Yen Ho, Yi-Shu Tai, I-Kuei Chen, Wei-Lun Huang, Che-Ping Chou, Tse-Ju Lin, Han-Jay Yang, Yen-Kai Wang, Cheng-Te Li, Shou-De Lin, and Hsuan-Tien Lin. A two-stage ensemble of diverse models for advertisement ranking in KDD Cup 2012. Technical report, National Taiwan University, August 2012. First-place winner report of KDD Cup 2012 track 2. [ bib | pdf ]
[KC2012] Ku-Chun Chou and Hsuan-Tien Lin. Balancing between estimated reward and uncertainty during news article recommendation for ICML 2012 exploration and exploitation challenge. Technical report, National Taiwan University, June 2012. First-place winner report of the Exploration and Exploitation Challenge @ ICML 2012 phase 1. [ bib | pdf ]
[HL2012b] Hsuan-Tien Lin, Malik Madgon-Ismail, and Yaser S. Abu-Mostafa. Teaching machine learning to a diverse audience: the foundation-based approach. Technical report, National Taiwan Unversity, June 2012. Presented in the Teaching Machine Learning Workshop @ ICML '12. [ bib | pdf ]
[SC2012] Shang-Tse Chen, Hsuan-Tien Lin, and Chi-Jen Lu. An online boosting algorithm with theoretical justifications. In Proceedings of the International Conference on Machine Learning (ICML), June 2012. [ bib | pdf ]
[HL2012a] Hsuan-Tien Lin and Ling Li. Reduction from cost-sensitive ordinal ranking to weighted binary classification. Neural Computation, 24(5):1329--1367, May 2012. Some preliminary parts appeared in NIPS '06 and PL Workshop @ ECML/PKDD '09. [ bib | pdf ]
[TM2012] 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. In Proceedings of the KDD Cup 2011 Workshop, volume 18 of JMLR Workshop and Conference Proceedings, pages 101--135, May 2012. First-place winner report of KDD Cup 2011 track 2. [ bib | pdf ]
[PC2012] 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. In Proceedings of the KDD Cup 2011 Workshop, volume 18 of JMLR Workshop and Conference Proceedings, pages 21--60, May 2012. First-place winner report of KDD Cup 2011 track 1. [ bib | pdf ]
[YA2012] Yaser S. Abu-Mostafa, Malik Magdon-Ismail, and Hsuan-Tien Lin. Learning from Data: A Short Course. AMLBook, March 2012. [ bib | http ]

2011

[CH2011] Chen-Wei Hung and Hsuan-Tien Lin. Multi-label active learning with auxiliary learner. In Proceedings of the Asian Conference on Machine Learning (ACML), volume 20 of JMLR Workshop and Conference Proceedings, pages 315--330, November 2011. [ bib | pdf ]
[CF2011] Chun-Sung Ferng and Hsuan-Tien Lin. Multi-label classification with error-correcting codes. In Proceedings of the Asian Conference on Machine Learning (ACML), volume 20 of JMLR Workshop and Conference Proceedings, pages 281--295, November 2011. [ bib | pdf ]
[TJ2011] 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 the IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pages 390--393, November 2011. [ bib | pdf ]
[YK2011] 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), pages 905--912, June 2011. [ bib | pdf ]

2010

[HL2010] Hsuan-Tien Lin. Cost-sensitive classification: Status and beyond. Technical report, National Taiwan University, November 2010. Presented in the Workshop on Machine Learning Research in Taiwan: Challenges and Directions @ TAAI '10. [ bib | pdf ]
[HY2010] 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. In Proceedings of the KDD Cup 2010 Workshop, July 2010. First-place winner report of KDD Cup 2010. [ bib | pdf ]
[MT2010] 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. Technical report, National Taiwan University, June 2010. Presented in the Workshop of Yahoo! Learning to Rank Challenge @ ICML '10. [ bib | pdf ]
[FT2010a] Farbound Tai and Hsuan-Tien Lin. Multi-label classification with principle label space transformation. In Proceedings of the 2nd International Workshop on learning from Multi-Label Data @ ICML '10, June 2010. [ bib | pdf ]
[HT2010] Han-Hsing Tu and Hsuan-Tien Lin. One-sided support vector regression for multiclass cost-sensitive classification. In Proceedings of the 27th International Conference on Machine Learning (ICML), pages 1095--1102, June 2010. [ bib | pdf ]

2009

[HL2009] Hsuan-Tien Lin and Ling Li. Combining ordinal preferences by boosting. In Proceedings of the Preference Learning Workshop in ECML/PKDD '09, pages 69--83, September 2009. [ bib | pdf ]
[HLo2009] 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 Proceedings of KDD-Cup 2009 competition, volume 7 of JMLR Workshop and Conference Proceedings, pages 57--64, June 2009. Third-place winner report of KDD Cup 2009 slow track. [ bib | pdf ]

Before 2008 (Ph.D. Student at Caltech)

[HL2008b] Hsuan-Tien Lin. From Ordinal Ranking to Binary Classification. PhD thesis, California Institute of Technology, June 2008. [ bib | pdf ]
[HL2008a] Hsuan-Tien Lin and Ling Li. Support vector machinery for infinite ensemble learning. Journal of Machine Learning Research, 9(2):285--312, February 2008. Some preliminary parts appeared in ECML '05 and ICONIP '05. [ bib | pdf ]
[HL2007] 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, August 2007. [ bib | pdf ]
[LL2007] Ling Li and Hsuan-Tien Lin. Optimizing 0/1 loss for perceptrons by random coordinate descent. In Proceedings of the 2007 International Joint Conference on Neural Networks (IJCNN), pages 749--754, August 2007. [ bib | pdf ]
[LL2006] Ling Li and Hsuan-Tien Lin. Ordinal regression by extended binary classification. In Advances in Neural Information Processing Systems : Proceedings of the 2006 Conference (NIPS), pages 865--872, December 2006. [ bib | pdf ]
[HL2006] Hsuan-Tien Lin and Ling Li. Large-margin thresholded ensembles for ordinal regression: Theory and practice. In Algorithmic Learning Theory (ALT), volume 4264 of Lecture Notes in Artificial Intelligence, pages 319--333, October 2006. [ bib | pdf ]
[HL2005d] Hsuan-Tien Lin and Ling Li. Novel distance-based SVM kernels for infinite ensemble learning. In Proceedings of the 12th International Conference on Neural Information Processing (ICONIP), pages 761--766, November 2005. [ bib | pdf ]
[HL2005c] Hsuan-Tien Lin and Ling Li. Analysis of SAGE results with combined learning techniques. In Proceedings of the ECML/PKDD 2005 Discovery Challenge, pages 102--113, November 2005. [ bib | pdf ]
[LL2005] Ling Li, Amrit Pratap, Hsuan-Tien Lin, and Yaser S. Abu-Mostafa. Improving generalization by data categorization. In Knowledge Discovery in Databases (PKDD), volume 3721 of Lecture Notes in Computer Science, pages 157--168, November 2005. [ bib | pdf ]
[HL2005b] Hsuan-Tien Lin and Ling Li. Infinite ensemble learning with support vector machines. In Machine Learning: Proceedings of the 16th European Conference on Machine Learning (ECML), volume 3720 of Lecture Notes in Computer Science, pages 242--254, October 2005. [ bib | pdf ]
[HL2005a] Hsuan-Tien Lin. Infinite ensemble learning with support vector machines. Master's thesis, California Institute of Technology, June 2005. [ bib | pdf ]

Before 2003 (Student/RA at NTU)

[HL2003] 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. Technical report, National Taiwan University, March 2003. [ bib | pdf ]
[SL2002] 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, June 2002. A preliminary version appeared in IJCNN '01. [ bib | pdf ]
[SL2001] Shuo-Peng Liao, Hsuan-Tien Lin, and Chih-Jen Lin. A note on the decomposition methods for support vector regression. In Proceedings of the 2001 International Joint Conference on Neural Networks (IJCNN), pages 1474--1479, July 2001. [ bib | pdf ]

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