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Journal Article (8)

1.
Journal Article
Weston, J.; Leslie, C.; Ie, E.; Zhou, D.; Elisseeff, A.; Noble, W.: Semi-supervised protein classification using cluster kernels. Bioinformatics 21 (15), pp. 3241 - 3247 (2005)
2.
Journal Article
Guermeur, J.; Elisseeff, A.; Zelus, D.: A comparative study of multi-class support vector machines in the unifying framework of large margin classifiers. Applied Stochastic Models in Business and Industry 21 (2), pp. 199 - 214 (2005)
3.
Journal Article
Evgeniou, T.; Pontil, M.; Elisseeff, A.: Leave One Out Error, Stability, and Generalization of Voting Combinations of Classifiers. Machine Learning 55 (1), pp. 71 - 97 (2004)
4.
Journal Article
Weston, J.; Elisseeff, A.; Zhou, D.; Leslie, C.; Noble, W.: Protein ranking: from local to global structure in the protein similarity network. Proceedings of the National Academy of Sciences of the United States of America 101 (17), pp. 6559 - 6563 (2004)
5.
Journal Article
Weston, J.; Perez-Cruz, F.; Bousquet, O.; Chapelle, O.; Elisseeff, A.; Schölkopf, B.: Feature selection and transduction for prediction of molecular bioactivity for drug design. Bioinformatics 19 (6), pp. 764 - 771 (2003)
6.
Journal Article
Guyon, I.; Elisseeff, A.: An Introduction to Variable and Feature Selection. The Journal of Machine Learning Research 3, pp. 1157 - 1182 (2003)
7.
Journal Article
Weston, J.; Elisseeff, A.; Schölkopf, B.; Tipping, M.: Use of the Zero-Norm with Linear Models and Kernel Methods. The Journal of Machine Learning Research 3, pp. 1439 - 1461 (2003)
8.
Journal Article
Bousquet, O.; Elisseeff, A.: Stability and Generalization. The Journal of Machine Learning Research 2, pp. 499 - 526 (2002)

Book Chapter (2)

9.
Book Chapter
Lal, T.; Chapelle, O.; Weston, J.; Elisseeff, A.: Embedded methods. In: Feature Extraction: Foundations and Applications, pp. 137 - 165 (Eds. Guyon, I.; Gunn, S.; Nikravesh, M.; Zadeh, L.). Springer, Berlin, Germany (2006)
10.
Book Chapter
Smola, A.; Elisseeff, A.; Schölkopf, B.; Williamson, R.: Entropy numbers for convex combinations and MLPs. In: Advances in Large Margin Classifiers, pp. 369 - 387 (Eds. Smola, A.; Bartlett, P.; Schölkopf, B.; Schuurmans, D.). MIT Press, Cambridge, MA, USA (2000)

Conference Paper (5)

11.
Conference Paper
Weston, J.; Leslie, C.; Zhou, D.; Elisseeff, A.; Noble, W.: Semi-Supervised Protein Classification using Cluster Kernels. Seventeenth Annual Conference on Neural Information Processing Systems (NIPS 2003), Vancouver, BC, Canada, December 09, 2003 - December 11, 2003. Advances in Neural Information Processing Systems 16, pp. 595 - 602 (2004)
12.
Conference Paper
Weston, J.; Chapelle, O.; Elisseeff, A.; Schölkopf, B.; Vapnik, V.: Kernel Dependency Estimation. In: Advances in Neural Information Processing Systems 15, pp. 873 - 880 (Eds. Becker, S.; Thrun, S.; Obermayer, K.). Sixteenth Annual Conference on Neural Information Processing Systems (NIPS 2002), Vancouver, BC, Canada, December 09, 2002 - December 14, 2002. MIT Press, Cambridge, MA, USA (2003)
13.
Conference Paper
Elisseeff, A.; Pontil, M.: Stability of ensembles of kernel machines. In: Advances in learning theory: methods, models and applications, pp. 111 - 124 (Eds. Suykens, J.; Horvath, G.; Basu, S.; Micchelli, C.; Vandewalle, J.). NATO Advanced Study Institute on Learning Theory and Practice 2002, Leuven, Belgium, July 08, 2002 - July 19, 2002. IOS Press, Amsterdam, The Netherlands (2003)
14.
Conference Paper
Weston, J.; Perez-Cruz , F.; Bousquet, O.; Chapelle, O.; Elisseeff, A.; Schölkopf, B.: KDD Cup 2001 data analysis: prediction of molecular bioactivity for drug Design-Binding to Thrombin. In: KDD-2001 Cup: The Genomics Challenge. KDD-2001 Cup: The Genomics Challenge, August 26, 2001. (2001)
15.
Conference Paper
Bousquet, O.; Elisseeff, A.: Algorithmic Stability and Generalization Performance. In: Advances in Neural Information Processing Systems 13, pp. 196 - 202 (Eds. Leen, T.; Dietterich, T.; Tresp, V.). Fourteenth Annual Neural Information Processing Systems Conference (NIPS 2000), Denver, CO, USA, November 27, 2000 - December 02, 2000. MIT Press, Cambridge, MA, USA (2001)

Report (4)

16.
Report
Weston, J.; Leslie, C.; Elisseeff, A.; Noble, W.: Machine Learning approaches to protein ranking: discriminative, semi-supervised, scalable algorithms (Technical Report of the Max Planck Institute for Biological Cybernetics, 111). Max Planck Institute for Biological Cybernetics, Tübingen, Germany (2003), 10 pp.
17.
Report
Weston, J.; Chapelle, O.; Elisseeff, A.; Schölkopf, B.; Vapnik, V.: Kernel Dependency Estimation (Technical Report of the Max Planck Institute for Biological Cybernetics, 98). Max Planck Institute for Biological Cybernetics, Tübingen, Germany (2002), 10 pp.
18.
Report
Weston, J.; Perez-Cruz F, Bousquet, O.; Chapelle, O.; Elisseeff, A.; Schölkopf, B.: Feature Selection and Transduction for Prediction of Molecular Bioactivity for Drug Design. (2002)
19.
Report
Weston, J.; Elisseeff, A.; Schölkopf, B.: Use of the $ell_0$-norm with linear models and kernel methods. Biowulf Technologies, Savannah, GA, USA (2001)
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