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Journal Article (17)

1.
Journal Article
Graf, A.; Bousquet, O.; Rätsch, G.; Schölkopf, B.: Prototype Classification: Insights from Machine Learning. Neural computation 21 (1), pp. 272 - 300 (2009)
2.
Journal Article
von Luxburg, U.; Belkin, M.; Bousquet, O.: Consistency of Spectral Clustering. The Annals of Statistics 36 (2), pp. 555 - 586 (2008)
3.
Journal Article
Bousquet, O.; Schölkopf, B.: Comment. Statistical Science 21 (3), pp. 337 - 340 (2006)
4.
Journal Article
Blanchard, G.; Bousquet, O.; Zwald, L.: Statistical Properties of Kernel Principal Component Analysis. Machine Learning 66 (2-3), pp. 259 - 294 (2006)
5.
Journal Article
Gretton, A.; Herbrich, R.; Smola, A.; Bousquet, O.; Schölkopf, B.: Kernel Methods for Measuring Independence. The Journal of Machine Learning Research 6, pp. 2075 - 2129 (2005)
6.
Journal Article
Hein, M.; Bousquet, O.; Schölkopf, B.: Maximal Margin Classification for Metric Spaces. Journal of Computer and System Sciences 71 (3), pp. 333 - 359 (2005)
7.
Journal Article
Bartlett, P.; Bousquet, O.; Mendelson, S.: Local Rademacher Complexities. The Annals of Statistics 33 (4), pp. 1497 - 1537 (2005)
8.
Journal Article
Boucheron, S.; Bousquet, O.; Lugosi, G.: Theory of Classification: A Survey of Some Recent Advances. ESAIM: Probability and Statistics 9, pp. 323 - 375 (2005)
9.
Journal Article
Boucheron, S.; Bousquet, O.; Lugosi, G.; Massart, P.: Moment Inequalities for Functions of Independent Random Variables. Annals of Probability 33 (2), pp. 514 - 560 (2005)
10.
Journal Article
von Luxburg, U.; Bousquet, O.: Distance-Based Classification with Lipschitz Functions. The Journal of Machine Learning Research 5, pp. 669 - 695 (2004)
11.
Journal Article
Perez-Cruz, F.; Bousquet, O.: Kernel Methods and their Potential Use in Signal Processing. IEEE Signal Processing Magazine 21 (3), pp. 57 - 65 (2004)
12.
Journal Article
Blanchard, G.; Bousquet, O.; Massart, P.: Statistical Performance of Support Vector Machines. The Annals of Statistics 36 (2), pp. 489 - 531 (2004)
13.
Journal Article
von Luxburg, U.; Bousquet, O.; Schölkopf, B.: A Compression Approach to Support Vector Model Selection. The Journal of Machine Learning Research 5, pp. 293 - 323 (2004)
14.
Journal Article
Bousquet, O.: New Approaches to Statistical Learning Theory. Annals of the Institute of Statistical Mathematics 55 (2), pp. 371 - 389 (2003)
15.
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)
16.
Journal Article
Bousquet, O.: Tracking a Small Set of Experts by Mixing Past Posteriors. The Journal of Machine Learning Research 3, pp. 363 - 396 (2002)
17.
Journal Article
Bousquet, O.; Elisseeff, A.: Stability and Generalization. The Journal of Machine Learning Research 2, pp. 499 - 526 (2002)

Book Chapter (2)

18.
Book Chapter
Weston, J.; Bakir, G.; Bousquet, O.; Mann, T.; Noble, W.; Schölkopf, B.: Joint Kernel Maps. In: Predicting Structured Data, pp. 67 - 84 (Eds. Bakır, G.; Hofmann, T.; Schölkopf, B.; Smola, A.; Taskar, B. et al.). MIT Press, Cambridge, MA, USA (2007)
19.
Book Chapter
Bousquet, O.: Concentration Inequalities for Sub-Additive Functions Using the Entropy Method. In: Stochastic Inequalities and Applications, Vol. 56, pp. 213 - 247 (Eds. Giné, E.; Houdré, C.; Nualart, D.). Birkhäuser, Basel, Switzerland (2003)

Proceedings (1)

20.
Proceedings
Advanced Lectures on Machine Learning: ML Summer Schools 2003, Canberra, Australia, February 2 - 14, 2003, Tübingen, Germany, August 4 - 16, 2003 (Lecture Notes in Computer Science, 3176). ML Summer Schools 2003, Canberra, Australia, February 02, 2004 - February 14, 2004. Springer, Berlin, Germany (2004), 240 pp.
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