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Dr. Olivier Bousquet

E-Mail:

obousquet[at]gmail.com

Olivier Bousquet

Position: Research Scientist Unit: Alumni Schölkopf

Publications

Proceedings (1):
•	Bousquet O , von Luxburg U and Rätsch G : Advanced Lectures on Machine Learning, ML Summer Schools 2003, 240, Springer, Berlin, Germany, (September-2004). 978-3-540-23122-6
Articles (21):
•	Graf ABA , Bousquet O , Rätsch G and Schölkopf B (January-2009) Prototype Classification: Insights from Machine Learning Neural Computation 21(1) 272-300.
•	von Luxburg U , Belkin M and Bousquet O (April-2008) Consistency of Spectral Clustering Annals of Statistics 36(2) 555-586.
•	Bousquet O and Schölkopf B (August-2006) Comment Statistical Science 21(3) 337-340.
•	Blanchard G , Bousquet O and Zwald L (March-2006) Statistical Properties of Kernel Principal Component Analysis Machine Learning 66(2-3) 259-294.
•	Gretton A , Herbrich R , Smola A , Bousquet O and Schölkopf B (December-2005) Kernel Methods for Measuring Independence Journal of Machine Learning Research 6 2075-2129.
•	Hein M , Bousquet O and Schölkopf B (October-2005) Maximal Margin Classification for Metric Spaces Journal of Computer and System Sciences 71(3) 333-359.
•	Bartlett P , Bousquet O and Mendelson S (August-2005) Local Rademacher Complexities The Annals of Statistics 33(4) 1497-1537.
•	Boucheron S , Bousquet O , Lugosi G and Massart P (2005) Moment Inequalities for Functions of Independent Random Variables To appear in Annals of Probability 33 514-560.
•	Boucheron S , Bousquet O and Lugosi G (2005) Theory of Classification: A Survey of Some Recent Advances ESAIM: Probability and Statistics 9 323.
•	von Luxburg U and Bousquet O (June-2004) Distance-Based Classification with Lipschitz Functions Journal of Machine Learning Research 5 669-695.
•	von Luxburg U , Bousquet O and Schölkopf B (April-2004) A Compression Approach to Support Vector Model Selection The Journal of Machine Learning Research 5 293-323.
•	Blanchard G , Bousquet O and Massart P (2004) Statistical Performance of Support Vector Machines .
•	Perez-Cruz F and Bousquet O (2004) Kernel Methods and their Potential Use in Signal Processing IEEE Signal Processing Magazine (Special issue on Signal Processing for Mining). accepted
•	Bousquet O (November-2003) Concentration Inequalities for Sub-Additive Functions Using the Entropy Method Stochastic Inequalities and Applications 56 213-247.
•	Weston J , Perez-Cruz F , Bousquet O , Chapelle O , Elisseeff A and Schölkopf B (April-2003) Feature selection and transduction for prediction of molecular bioactivity for drug design Bioinformatics 19(6) 764-771.
•	Bousquet O (2003) New Approaches to Statistical Learning Theory Annals of the Institute of Statistical Mathematics 55(2) 371-389.
•	Bousquet O (2002) A Bennett Concentration Inequality and Its Application to Suprema of Empirical Processes C. R. Acad. Sci. Paris, Ser. I 334 495-500.
•	Chapelle O , Vapnik V , Bousquet O and Mukherjee S (2002) Choosing Multiple Parameters for Support Vector Machines Machine Learning 46(1) 131-159.
•	Bousquet O and Elisseeff A (2002) Stability and Generalization Journal of Machine Learning Research 2 499-526.
•	Bousquet O and Warmuth M (2002) Tracking a Small Set of Experts by Mixing Past Posteriors Journal of Machine Learning Research 3 363-396.
•	Balakrishnan K , Bousquet O and Honavar V (1999) Spatial Learning and Localization in Animals: A Computational Model and Its Implications for Mobile Robots Adaptive Behavior 7(2) 173-216.
Conference papers (21):
•	Quinonero Candela J , Rasmussen CE , Sinz F , Bousquet O and Schölkopf B (April-2006) Evaluating Predictive Uncertainty Challenge In: Machine Learning Challenges: Evaluating Predictive Uncertainty, Visual Object Classification, and Recognising Tectual Entailment, First PASCAL Machine Learning Challenges Workshop (MLCW 2005), Springer, Berlin, Germany, 1-27.
•	Gretton A , Bousquet O , Smola A and Schoelkopf B (October-8-2005) Measuring Statistical Dependence with Hilbert-Schmidt Norms In: Algorithmic Learning Theory: 16th International Conference, ALT 2005, ALT 2005, 63-78.
•	von Luxburg U , Bousquet O and Belkin M (July-2005) Limits of Spectral Clustering In: Advances in Neural Information Processing Systems 17, Eighteenth Annual Conference on Neural Information Processing Systems (NIPS 2004), MIT Press, Cambridge, MA, USA, 857-864.
•	Hein M and Bousquet O (January-2005) Hilbertian metrics and positive definite kernels on probability measures AISTATS, 136-143.
•	Gretton A , Smola AJ , Bousquet O , Herbrich R , Belitski A , Augath M , Murayama Y , Pauls J , Schölkopf B and Logothetis NK (January-2005) Kernel Constrained Covariance for Dependence Measurement AISTATS 2005, 10, 1-8.
•	Weston J , Schölkopf B and Bousquet O (2005) Joint Kernel Maps IWANN 2005, Springer-Verlag, Berlin Heidelberg, Germany, LNCS 3512, 176-191.
•	Zhou D , Bousquet O , Lal TN , Weston J and Schölkopf B (June-2004) Learning with Local and Global Consistency In: Advances in Neural Information Processing Systems 16, Seventeenth Annual Conference on Neural Information Processing Systems (NIPS 2003), MIT Press, Cambridge, MA, USA, 321-328.
•	Bousquet O , Chapelle O and Hein M (June-2004) Measure Based Regularization In: Advances in Neural Information Processing Systems 16, Seventeenth Annual Conference on Neural Information Processing Systems (NIPS 2003), MIT Press, Cambridge, MA, USA, 1221-1228.
•	Audibert J-Y and Bousquet O (June-2004) PAC-Bayesian Generic Chaining In: Advances in Neural Information Processing Systems 16, Seventeenth Annual Conference on Neural Information Processing Systems (NIPS 2003), MIT Press, Cambridge, MA, USA, 1125-1132.
•	Zhou D , Weston J , Gretton A , Bousquet O and Schölkopf B (June-2004) Ranking on Data Manifolds In: Advances in neural information processing systems 16, Seventeenth Annual Conference on Neural Information Processing Systems (NIPS 2003), MIT Press, Cambridge, MA, USA, 169-176.
•	Hein M and Bousquet O (February-2004) Maximal Margin Classification for Metric Spaces 16. Annual Conference on Computational Learning Theory / COLT Kernel 2003, Springer Verlag, Heidelberg, Germany, 72-86.
•	Hein H , Lal TN and Bousquet O (2004) Hilbertian Metrics on Probability Measures and their Application in SVM's Pattern Recognition, Proceedings of th 26th DAGM Symposium, 3175, 270-277.
•	von Luxburg U , Bousquet O and Belkin M (2004) On the Convergence of Spectral Clustering on Random Samples: The Normalized Case Proceedings of the 17th Annual Conference on Learning Theory, 457-471.
•	Bousquet O and Herrmann D (October-2003) On the Complexity of Learning the Kernel Matrix In: Advances in Neural Information Processing Systems 15, Sixteenth Annual Conference on Neural Information Processing Systems (NIPS 2002), The MIT Press, Cambridge, MA, USA, 399-406.
•	von Luxburg U and Bousquet O (2003) Distance-based classification with Lipschitz functions Learning Theory and Kernel Machines, Proceedings of the 16th Annual Conference on Computational Learning Theory, 314-328.
•	Bousquet O and Perez-Cruz F (2003) Kernel Methods and Their Applications to Signal Processing In: Proceedings. (ICASSP ‘03), ICASSP 2003, Special Session on Kernel Methods, 860.
•	Bartlett P , Bousquet O and Mendelson S (2002) Localized Rademacher Complexities Proceedings of the 15th annual conference on Computational Learning Theory, 44-58.
•	Bousquet O , Koltchinskii V and Panchenko D (2002) Some Local Measures of Complexity of Convex Hulls and Generalization Bounds Proceedings of the 15th annual conference on Computational Learning Theory.
•	Bousquet O and Elisseeff A (April-2001) Algorithmic Stability and Generalization Performance In: Advances in Neural Information Processing Systems 13, Fourteenth Annual Neural Information Processing Systems Conference (NIPS 2000), MIT Press, Cambridge, MA, USA, 196-202.
•	Bousquet O and Warmuth M (2001) Tracking a Small Set of Experts by Mixing Past Posteriors Proceedings of the 14th Annual Conference on Computational Learning Theory, Lecture Notes in Computer Science, 2111, 31-47.
•	Bousquet O , Balakrishnan K and Honavar V (1999) Is the Hippocampus a Kalman Filter? Proceedings of the Pacific Symposium on Biocomputing, 3, 619-630.
Contributions to books (3):
•	Weston J , Bakir GH , Bousquet O , Mann T , Noble WS and Schölkopf B : Joint Kernel Maps, 67-84. In: Predicting Structured Data, (Ed) G. H. Bakir, MIT Press, Cambridge, MA, USA, (September-2007).
•	Boucheron S , Lugosi G and Bousquet O : Concentration Inequalities, 208-240. (Ed) O. Bousquet and G. Rätsch, Springer, Heidelberg, Germany, (2004).
•	Bousquet O , Boucheron S and Lugosi G : Introduction to Statistical Learning Theory, 169-207. (Ed) O. Bousquet and G. Rätsch, Springer, Heidelberg, Germany, (2004).
Technical reports (12):
•	Gretton A , Bousquet O , Smola AJ and Schölkopf B : Measuring Statistical Dependence with Hilbert-Schmidt Norms, 140, Max Planck Institute for Biological Cybernetics, Tübingen, Germany, (June-2005).
•	von Luxburg U , Belkin M and Bousquet O : Consistency of Spectral Clustering, 134, (December-2004).
•	Weston J , Schölkopf B , Bousquet O , Mann and Noble WS : Joint Kernel Maps, 131, Max-Planck-Institute for Biological Cybernetics, Tübingen, (November-2004).
•	Hein M and Bousquet O : Hilbertian Metrics and Positive Definite Kernels on Probability Measures, 126, (July-2004).