Talks

• Label Space Coding for Multi-label Classification. IIS Sinica Seminar, Taipei, Taiwan, April 2012.
• Multi-label Active Learning with Auxiliary Learner. ACML 2011, Taoyuan, Taiwan, November 2011. (Paper).
• Cost-sensitive Multiclass Classification via Regression. NCCU CS Seminar, Taipei, Taiwan, November 2011.
• Research in the Computational Learning Laboratory: Ordinal Ranking, Cost-sensitive Classification and KDDCup 2011. Plaxie, Taipei, Taiwan, November 2011.
• Solutions and Experiences from KDD Cup 2011: A Linear Ensemble of Individual and Blended Models for Music Rating Prediction. CITI Sinica Seminar, Taipei, Taiwan, October 2011.
• A Linear Ensemble of Individual and Blended Models for Music Rating Prediction. KDDCup 2011, San Diego, CA, USA, August 2011. (Paper)
• Cost-sensitive Multiclass Classification via Regression. NTNU CSIE Seminar, Taipei, Taiwan, December 2010.
• Cost-sensitive Classification: Status and Beyond. Machine Learning Research in Taiwan@TAAI 2010, Hsinchu, Taiwan, November 2010. (Paper).
• An Ensemble Solution for Learning to Rank. Yahoo! Learning to Rank Challenge@ICML 2010, Haifa, Israel, June 2010. (Paper)
• One-sided Support Vector Regression for Multiclass Cost-sensitive Classification. ICML 2010, Haifa, Israel, June 2010. (Paper).
• Cost-sensitive Multiclass Classification via Regression. CITI Sinica Seminar, Taipei, Taiwan, May 2010.
• Cost-sensitive Multiclass Classification Using One-versus-one Comparisons. NTHU EE Seminar, Hsinchu, Taiwan, April 2010.
• From Ordinal Ranking to Binary Classification. NDHU AM Seminar, Hualian, Taiwan, February 2010.
• Combining Ordinal Preferences by Boosting. Preference Learning Workshop @ ECML/PKDD 2009, Bled, Slovenia, September 2009. (Paper).
• From Ordinal Ranking to Binary Classification. NTUST CS Seminar, Taipei, Taiwan, March 2009.
• From Ordinal Ranking to Binary Classification. Microsoft Research Asia, Beijing, China, February 2009.
• A Simple Algorithm for Cost-Sensitive Classification. NTU CSIE Seminar, Taipei, Taiwan, September 2008.
• From Ordinal Ranking to Binary Classification. NTHU CS Seminar, Hsinchu, Taiwan, March 2008.
• From Ordinal Ranking to Binary Classification. NCTU CS Seminar, Hsinchu, Taiwan, March 2008.
• From Ordinal Ranking to Binary Classification. NTU CSIE Seminar, Taipei, Taiwan, March 2008.
• From Ordinal Ranking to Binary Classification. Caltech CS/IST Lunch Bunch, Pasadena, CA, U.S.A., March 2008.
• Perceptron Learning by Random Coordinate Descent. IJCNN '07, Orlando, FL, U.S.A., August 2007. (Paper).
• Automatic Ranking by Extended Binary Classification. Institute of Information Science, Academia Sinica, Taipei, Taiwan, March 2007.
• Ordinal Regression by Extended Binary Classification. NIPS '06 Spotlight, Vancouver, Canada, December 2006. (Poster), (Paper).
• Automatic Ranking by Extended Binary Classification. Caltech EE Fall '06 Seminar, Pasadena, CA, U.S.A., November 2006.
• Large-Margin Thresholded Ensembles for Ordinal Regression. ALT '06, Barcelona, Spain, October 2006. (Paper).
• Large-Margin Thresholded Ensembles for Ordinal Regression. MLSS '06 Workshop, Taipei, Taiwan, July 2006.
• Distance Based SVM Kernels for Infinite Ensemble Learning. ICONIP '05, Taipei, Taiwan, November 2005. (Paper).
• Analysis of SAGE Results with Combined Learning Techniques. ECML/PKDD Discovery Challenge Workshop '05, Porto, Portugal, October 2005. (Paper).
• Infinite Ensemble Learning with Support Vector Machinery. ECML '05, Porto, Portugal, October 2005. (Paper).
• Infinite Ensemble Learning with Support Vector Machines. Caltech Second Symposium on Vision and Learning, Pasadena, CA, U.S.A., September 2005.

Posters

• Ordinal Regression by Extended Binary Classification. NIPS '06, Vancouver, Canada, December 2006. (Spotlight), (Paper).

Lectures

• Brief Introduction to LEMGA. Minitalk for Caltech CS 156b (Winter '06): Learning Systems, Pasadena, CA, U.S.A., January 2006. (Software).
• Introduction to Support Vector Machines. Invited talk for NTU Speech Processing Lab, Taipei, Taiwan, November 2005.
• Introduction to Boosting and Joint Boosting. Guest lecture for Caltech EE148 (Spring '05): Machine Learning for Computer Vision, Pasadena, CA, U.S.A., April 2005.

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