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Dr. Olivier Bousquet

 

Bild von Bousquet, Olivier, Dr.

Olivier Bousquet

Position: Wissenschaftler  Abteilung: 

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Tagungsbände (1):

Bousquet O, von Luxburg U und Rätsch G: Advanced Lectures on Machine Learning, ML Summer Schools 2003, 240, Springer, Berlin, Germany, (September-2004).
978-3-540-23122-6, Series: Lecture Notes in Computer Science ; 3176

Artikel (20):

Graf ABA, Bousquet O, Rätsch G und Schölkopf B (Januar-2009) Prototype Classification: Insights from Machine Learning Neural Computation 21(1) 272-300.
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von Luxburg U, Belkin M und Bousquet O (April-2008) Consistency of Spectral Clustering Annals of Statistics 36(2) 555-586.
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Bousquet O und Schölkopf B (August-2006) Comment Statistical Science 21(3) 337-340.
Blanchard G, Bousquet O und Zwald L (März-2006) Statistical Properties of Kernel Principal Component Analysis Machine Learning 66(2-3) 259-294.
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Gretton A, Herbrich R, Smola A, Bousquet O und Schölkopf B (Dezember-2005) Kernel Methods for Measuring Independence Journal of Machine Learning Research 6 2075-2129.
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Hein M, Bousquet O und Schölkopf B (Oktober-2005) Maximal Margin Classification for Metric Spaces Journal of Computer and System Sciences 71(3) 333-359.
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Bartlett P, Bousquet O und Mendelson S (August-2005) Local Rademacher Complexities Annals of Statistics 33(4) 1497-1537.
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Boucheron S, Bousquet O und Lugosi G (Juni-2005) Theory of Classification: A Survey of Some Recent Advances ESAIM: Probability and Statistics 9 323-375.
Boucheron S, Bousquet O, Lugosi G und Massart P (März-2005) Moment Inequalities for Functions of Independent Random Variables Annals of Probability 33(2) 514-560.
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von Luxburg U und Bousquet O (Juni-2004) Distance-Based Classification with Lipschitz Functions Journal of Machine Learning Research 5 669-695.
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Perez-Cruz F und Bousquet O (Mai-2004) Kernel methods and their potential use in signal processing IEEE Signal Processing Magazine 21(3) 57-65.
von Luxburg U, Bousquet O und 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 und Massart P (April-2004) Statistical Performance of Support Vector Machines Annals of Statistics 36(2) 489-531.
Bousquet O (Juni-2003) New Approaches to Statistical Learning Theory Annals of the Institute of Statistical Mathematics 55(2) 371-389.
Weston J, Perez-Cruz F, Bousquet O, Chapelle O, Elisseeff A und Schölkopf B (April-2003) Feature selection and transduction for prediction of molecular bioactivity for drug design Bioinformatics 19(6) 764-771.
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.
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Chapelle O, Vapnik V, Bousquet O und Mukherjee S (2002) Choosing Multiple Parameters for Support Vector Machines Machine Learning 46(1) 131-159.
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Bousquet O und Elisseeff A (2002) Stability and Generalization Journal of Machine Learning Research 2 499-526.
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Bousquet O und Warmuth M (2002) Tracking a Small Set of Experts by Mixing Past Posteriors Journal of Machine Learning Research 3 363-396.
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Balakrishnan K, Bousquet O und Honavar V (1999) Spatial Learning and Localization in Animals: A Computational Model and Its Implications for Mobile Robots Adaptive Behavior 7(2) 173-216.

Beiträge zu Tagungsbänden (25):

Quinonero Candela J, Rasmussen CE, Sinz F, Bousquet O und 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, Series: Lecture Notes in Computer Science ; 3944.
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Gretton A, Bousquet O, Smola A und Schölkopf B (Oktober-2005) Measuring Statistical Dependence with Hilbert-Schmidt Norms In: Algorithmic Learning Theory, , 16th International Conference on Algorithmic Learning Theory (ALT 2005), Springer, Berlin, Germany, 63-78, Series: Lecture Notes in Computer Science ; 3734.
von Luxburg U, Bousquet O und Belkin M (Juli-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.
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Candillier L, Tellier I, Torre F und Bousquet O (Juli-2005) SSC: Statistical Subspace Clustering In: Machine Learning and Data Mining in Pattern Recognition, , 4th International Conference on Machine Learning and Data Mining in Pattern Recognition (MLDM 2005), Springer, Berlin, Germany, 100-109, Series: Lecture Notes in Computer Science ; 3587.
Weston J, Schölkopf B und Bousquet O (Juni-2005) Joint Kernel Maps In: Computational Intelligence and Bioinspired Systems, , 8th International Work-Conference on Artificial Neural Networks (IWANN 2005), Springer, Berlin, Germany, 176-191, Series: Lecture Notes in Computer Science ; 3512.
Hein M und Bousquet O (Januar-2005) Hilbertian Metrics and Positive Definite Kernels on Probability Measures, Tenth International Workshop on Artificial Intelligence and Statistics (AISTATS 2005), Society for Artificial Intelligence and Statistics, Fort Lauderdale, FL, USA, 136-143.
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Gretton A, Smola AJ, Bousquet O, Herbrich R, Belitski A, Augath M, Murayama Y, Pauls J, Schölkopf B und Logothetis NK (Januar-2005) Kernel Constrained Covariance for Dependence Measurement, Tenth International Workshop on Artificial Intelligence and Statistics (AISTATS 2005), Society for Artificial Intelligence and Statistics, Fort Lauderdale, FL, USA, 112-119.
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Boucheron S, Lugosi G und Bousquet O (September-2004) Concentration Inequalities In: Advanced Lectures on Machine Learning, , ML Summer Schools 2003, Springer, Berlin, Germany, 208-240, Series: Lecture Notes in Computer Science ; 3176.
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Hein H, Lal TN und Bousquet O (September-2004) Hilbertian Metrics on Probability Measures and their Application in SVM's In: Pattern Recognition, , 26th Annual Symposium of the German Association for Pattern Recognition (DAGM 2004), Springer, Berlin, Germany, 270-277, Series: Lecture Notes in Computer Science ; 3175.
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Bousquet O, Boucheron S und Lugosi G (September-2004) Introduction to Statistical Learning Theory In: Advanced Lectures on Machine Learning, , ML Summer Schools 2003, Springer, Berlin, Germany, 169-207, Series: Lecture Notes in Computer Science ; 3176.
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von Luxburg U, Bousquet O und Belkin M (Juli-2004) On the Convergence of Spectral Clustering on Random Samples: The Normalized Case In: Learning Theory, , 17th Annual Conference on Learning Theory (COLT 2004), Springer, Berlin, Germany, 457-471, Series: Lecture Notes in Computer Science ; 3120.
Zwald L, Bousquet O und Blanchard G (Juli-2004) Statistical Properties of Kernel Principal Component Analysis In: Learning Theory, , 17th Annual Conference on Learning Theory (COLT 2004), Springer, Berlin, Germany, 594-608, Series: Lecture Notes in Computer Science ; 3120.
Zhou D, Bousquet O, Lal TN, Weston J und Schölkopf B (Juni-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.
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Bousquet O, Chapelle O und Hein M (Juni-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.
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Audibert J-Y und Bousquet O (Juni-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.
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Zhou D, Weston J, Gretton A, Bousquet O und Schölkopf B (Juni-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.
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Bousquet O und Herrmann D (Oktober-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.
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von Luxburg U und Bousquet O (August-2003) Distance-Based Classification with Lipschitz Functions In: Learning Theory and Kernel Machines, , 16th Annual Conference on Learning Theory and 7th Kernel Workshop (COLT/Kernel 2003), Springer, Berlin, Germany, 314-328, Series: Lecture Notes in Computer Science ; 2777.
Hein M und Bousquet O (August-2003) Maximal Margin Classification for Metric Spaces In: Learning Theory and Kernel Machines, , 16th Annual Conference on Learning Theory and 7th Kernel Workshop (COLT/Kernel 2003), Springer, Berlin, Germany, 72-86, Series: Lecture Notes in Computer Science ; 2777.
Bousquet O und Perez-Cruz F (April-2003) Kernel methods and their applications to signal processing, IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '03), IEEE Operations Center, Piscataway, NJ, USA, 860-863.
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Bartlett P, Bousquet O und Mendelson S (Juli-2002) Localized Rademacher Complexities In: Computational Learning Theory, , 15th Annual Conference on Computational Learning Theory (COLT 2002), Springer, Berlin, Germany, 44-58, Series: Lecture Notes in Computer Science ; 2375.
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Bousquet O, Koltchinskii V und Panchenko D (Juli-2002) Some Local Measures of Complexity of Convex Hulls and Generalization Bounds In: Computational Learning Theory, , 15th Annual Conference on Computational Learning Theory (COLT 2002), Springer, Berlin, Germany, 59-73, Series: Lecture Notes in Computer Science ; 2375.
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Bousquet O und Warmuth M (Juli-2001) Tracking a Small Set of Experts by Mixing Past Posteriors In: Computational Learning Theory, , 14th Annual Conference on Computational Learning Theory (COLT 2001) and 5th European Conference on Computational Learning Theory (EuroCOLT 2001), Springer, Berlin, Germany, 31-47, Series: Lecture Notes in Computer Science ; 2111.
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Bousquet O und 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.
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Bousquet O, Balakrishnan K und Honavar V (1999) Is the Hippocampus a Kalman Filter?, Pacific Symposium on Biocomputing (PSB '99), World Scientific, Singapore, 619-630.

Beiträge zu Büchern (2):

Weston J, Bakir GH, Bousquet O, Mann T, Noble WS und Schölkopf B: Joint Kernel Maps, 67-83. In: Predicting Structured Data, (Ed) G. H. Bakir, MIT Press, Cambridge, MA, USA, (September-2007).
Bousquet O: Concentration Inequalities for Sub-Additive Functions Using the Entropy Method, 213-247. In: Stochastic Inequalities and Applications, (Ed) E. Giné und D. Nualart, Springer, Berlin, Germany, (2003).

Technische Berichte (11):

Gretton A, Bousquet O, Smola AJ und Schölkopf B: Measuring Statistical Dependence with Hilbert-Schmidt Norms, 140, Max Planck Institute for Biological Cybernetics, Tübingen, Germany, (Juni-2005).
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von Luxburg U, Belkin M und Bousquet O: Consistency of Spectral Clustering, 134, Max Planck Institute for Biological Cybernetics, Tübingen, Germany, (Dezember-2004).
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Last updated: Montag, 22.05.2017