Publications of M Wu

Wu, M.; Schölkopf, B.; BakIr, G.: A Direct Method for Building Sparse Kernel Learning Algorithms. The Journal of Machine Learning Research 7, pp. 603 - 624 (2006)

Ye, J.; Zhao, Z.; Wu, M.: Discriminative K-means for Clustering. In: Advances in Neural Information Processing Systems 20: 21st Annual Conference on Neural Information Processing Systems 2007, pp. 1649 - 1656 (Eds. Platt, C.; Koller, D.; Singer, Y.; Roweis, S.). Twenty-First Annual Conference on Neural Information Processing Systems (NIPS 2007), Vancouver, BC, Canada, December 03, 2007 - December 06, 2007. Curran, Red Hook, NY, USA (2008)

Wu, M.; Schölkopf, B.: A Local Learning Approach for Clustering. In: Advances in Neural Information Processing Systems 19, pp. 1529 - 1536 (Eds. Schölkopf, B.; Platt, J.; Hoffman, T.). Twentieth Annual Conference on Neural Information Processing Systems (NIPS 2006), Vancouver, BC, Canada, December 04, 2006 - December 07, 2006. MIT Press, Cambridge, MA, USA (2007)

Wu, M.: Collaborative Filtering via Ensembles of Matrix Factorizations. In: KDD Cup and Workshop 2007, pp. 43 - 47. KDD Cup and Workshop 2007, San Jose, CA, USA, August 12, 2007. (2007)

Wu, M.; Yu , K.; Yu, S.; Schölkopf, B.: Local Learning Projections. In: ICML '07: 24th International Conference on Machine Learning, pp. 1039 - 1046 (Ed. Ghahramani, Z.). 24th International Conference on Machine Learning (ICML 2007), Corvallis, OR, USA, June 20, 2007 - June 24, 2007. ACM Press, New York, NY, USA (2007)

Wu, M.; Schölkopf, B.: Transductive Classification via Local Learning Regularization. In: Artificial Intelligence and Statistics, 21-24 March 2007, San Juan, Puerto Rico, pp. 628 - 635 (Eds. Meila, M.; Shen, X.). 11th International Conference on Artificial Intelligence and Statistics (AISTATS 2007), San Juan, Puerto Rico, March 21, 2007 - March 24, 2007. International Machine Learning Society, Madison, WI, USA (2007)

Wu, M.; Farquhar, J.: A Subspace Kernel for Nonlinear Feature Extraction. In: IJCAI'07: 20th International Joint Conference on Artifical Intelligence, pp. 1125 - 1130 (Eds. Sangal, R.; Mehta, H.; Bagga, R.). 20th International Joint Conference on Artificial Intelligence (IJCAI-07), Hyderabad, India, January 06, 2007 - January 12, 2007. Morgan Kaufmann Publishers Inc., San Francisco, CA, USA (2007)

Yu, S.; Yu , K.; Tresp, V.; Kriegel, H.-P.; Wu, M.: Supervised Probabilistic Principal Component Analysis. In: KDD '06: Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 464 - 473 (Eds. Eliassi-Rad, T.; Ungar, L.; Craven, M.; Gunopulos, D.). 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Philadelphia, PA, USA, August 20, 2006 - August 23, 2006. ACM Press, New York, NY, USA (2006)

Wu, M.; Schölkopf, B.; BakIr, G.: Building Sparse Large Margin Classifiers. In: ICML '05: 22nd international conference on Machine learning, pp. 996 - 1003 (Eds. Dzeroski, S.; de Raedt, L.; Wrobel, S.). 22nd International Conference on Machine Learning (ICML 2005), Bonn, Germany, August 07, 2005 - August 11, 2005. ACM, New York, NY, USA (2005)

Wu, M.: Local Learning Algorithms for Transductive Classification, Clustering and Data Projection. Yahoo Inc., Santa Clara, CA, USA (2007)

Wu, M.; Schölkopf, B.; BakIr, G.: Building Sparse Large Margin Classifiers. The 22nd International Conference on Machine Learning (ICML 2005), Bonn, Germany (2005)

Bakır, G.; Wu, M.; Eichhorn, J.: Maximum-Margin Feature Combination for Detection and Categorization. Max Planck Institute for Biological Cybernetics, Tübingen, Germany (2005), 8 pp.