Publications of O Chapelle

Conference Paper (21)

21.
Conference Paper
Cawley, G.; Talbot, N.; Chapelle, O.: Estimating Predictive Variances with Kernel Ridge Regression. In: Machine Learning Challenges. Evaluating Predictive Uncertainty, Visual Object Classification, and Recognising Tectual Entailment: First PASCAL Machine Learning Challenges Workshop, MLCW 2005, Southampton, UK, April 11-13, 2005, pp. 56 - 77 (Eds. Quinonero-Candela, J.; Dagan, I.; Magnini, B.; D‘Alché-Buc, F.). First PASCAL Machine Learning Challenges Workshop (MLCW 2005), Southampton, UK, April 11, 2005 - April 13, 2005. Springer, Berlin, Germany (2006)
22.
Conference Paper
Laaksonen, J.; Larlus, D.; Schiele, B.; Everingham, M.; Zisserman, A.; Williams, C.; van Gool, L.; Allan, M.; Bishop, C.; Chapelle, O. et al.: The 2005 PASCAL Visual Object Classes Challenge. In: Machine Learning Challenges: Evaluating Predictive Uncertainty, Visual Object Classification, and Recognising Tectual Entailment First PASCAL Machine Learning Challenges Workshop, MLCW 2005, Southampton, UK, April 11-13, 2005, pp. 117 - 176 (Eds. Quiñonero-Candela, J.; Dagan, I.; Magnini, B.; d’Alché-Buc, F.). First PASCAL Machine Learning Challenges Workshop (MLCW 2005), Southampton, UK, April 11, 2005 - April 13, 2005. Springer, Berlin (2006)
23.
Conference Paper
Kowalczyk, A.; Chapelle, O.: An Analysis of the Anti-Learning Phenomenon for the Class Symmetric Polyhedron. In: Algorithmic Learning Theory: 16th International Conference, ALT 2005, Singapore, October 8-11, 2005, pp. 78 - 92 (Eds. Jain, S.; Simon, H.; Tomita, E.). 16th International Conference on Algorithmic Learning Theory (ALT 2005), Singapore, October 08, 2005 - October 11, 2005. Springer, Berlin, Germany (2005)
24.
Conference Paper
Walder, C.; Chapelle, O.; Schölkopf, B.: Implicit Surface Modelling as an Eigenvalue Problem. In: ICML '05: 22nd international conference on Machine learning, pp. 936 - 939 (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 Press, New York, NY, USA (2005)
25.
Conference Paper
Chapelle, O.: A Machine Learning Approach to Conjoint Analysis. In: Advances in Neural Information Processing Systems 17, pp. 257 - 264 (Eds. Saul, L.; Weiss, Y.; Bottou, L.). Eighteenth Annual Conference on Neural Information Processing Systems (NIPS 2004), Vancouver, BC, Canada, December 13, 2004 - December 16, 2004. MIT Press, Cambridge, MA, USA (2005)
26.
Conference Paper
Chapelle, O.: Active Learning for Parzen Window Classifier. In: AISTATS 2005: Tenth International Workshop onArtificial Intelligence and Statistics, pp. 49 - 56 (Eds. Cowell, R.; Ghahramani, Z.). Tenth International Workshop on Artificial Intelligence and Statistics (AI Statistics 2005), Barbados, January 06, 2005 - January 08, 2005. The Society for Artificial Intelligence and Statistics (2005)
27.
Conference Paper
Chapelle, O.; Zien, A.: Semi-Supervised Classification by Low Density Separation. In: AISTATS 2005: Tenth International Workshop onArtificial Intelligence and Statistics, pp. 57 - 64 (Eds. Cowell, R.; Ghahramani, Z.). Tenth International Workshop on Artificial Intelligence and Statistics (AI Statistics 2005), Barbados, January 06, 2005 - January 08, 2005. The Society for Artificial Intelligence and Statistics (2005)
28.
Conference Paper
Bousquet, O.; Chapelle, O.; Hein, M.: Measure Based Regularization. In: Advances in Neural Information Processing Systems 16, pp. 1221 - 1228 (Eds. Thrun, S.; Saul, L.; Schölkopf, B.). Seventeenth Annual Conference on Neural Information Processing Systems (NIPS 2003), Vancouver, BC, Canada, December 09, 2003 - December 11, 2003. MIT Press, Cambridge, MA, USA (2004)
29.
Conference Paper
Fröhlich, H.; Chapelle, O.; Schölkopf, B.: Feature Selection for Support Vector Machines Using Genetic Algorithms. In: 15th IEEE International Conference on Tools with Artificial Intelligence, Vol. 13, pp. 142 - 148. 15th IEEE International Conference on Tools with Artificial Intelligence 2003, Sacramento, CA, USA, November 05, 2003. IEEE Operations Center, Piscataway, NJ, USA (2003)
30.
Conference Paper
Chapelle, O.; Weston, J.; Schölkopf, B.: Cluster Kernels for Semi-Supervised Learning. In: Advances in Neural Information Processing Systems 15, pp. 585 - 592 (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)
31.
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)
32.
Conference Paper
Chapelle, O.; Schölkopf, B.; Weston, J.: Semi-Supervised Learning through Principal Directions Estimation. In: ICML 2003 Workshop on the Continuum from Labeled to Unlabeled Data in Machine Learning & Data Mining, pp. 1 - 7. ICML 2003 Workshop on the Continuum from Labeled to Unlabeled Data in Machine Learning & Data Mining, Washington, DC, USA, August 21, 2003. (2003)
33.
Conference Paper
Chapelle, O.; Schölkopf, B.: Incorporating Invariances in Non-Linear Support Vector Machines. In: Advances in Neural Information Processing Systems 14, pp. 609 - 616 (Eds. Dietterich, T.; Becker, S.; Ghahramani, Z.). Fifteenth Annual Neural Information Processing Systems Conference (NIPS 2001), Vancouver, BC, Canada, December 03, 2001 - December 08, 2001. MIT Press, Cambridge, MA, USA (2002)

Talk (2)

34.
Talk
Chapelle, O.: A taxonomy of semi-supervised learning algorithms. Yahoo!, Sunnyvale, CA, USA (2005)
35.
Talk
Chapelle, O.: Some thoughts about Gaussian Processes. NIPS 2005 Workshop on Open Problems in Gaussian Processes for Machine Learning, Whistler, BC, Canada (2005)

Thesis - PhD (1)

36.
Thesis - PhD
Chapelle, O.: Support Vector Machines: Induction Principle, Adaptive Tuning and Prior Knowledge. Dissertation, 180 pp., Universit ́e Pierre et Marie Curie: Paris VI, Paris, France (2004)

Report (6)

37.
Report
Walder, C.; Chapelle, O.: Learning with Transformation Invariant Kernels (Technical Report of the Max Planck Institute for Biological Cybernetics, 165). Max Planck Institute for Biological Cybernetics, Tübingen, Germany (2007), 12 pp.
38.
Report
Chapelle, O.: Training a Support Vector Machine in the Primal (Technical Report of the Max Planck Institute for Biological Cybernetics, 147). Max Planck Institute for Biological Cybernetics, Tübingen, Germany (2006), 15 pp.
39.
Report
Eichhorn, J.; Chapelle, O.: Object categorization with SVM: kernels for local features (Technical Report of the Max Planck Institute for Biological Cybernetics, 137). Max Planck Institute for Biological Cybernetics, Tübingen, Germany (2004), 9 pp.
40.
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.