Olivier Chapelle

Minmin Chen, Zhixiang Eddie Xu, Kilian Q. Weinberger, Olivier Chapelle, Dor Kedem: Classifier Cascade for Minimizing Feature Evaluation Cost. Journal of Machine Learning Research - Proceedings Track 22: 218-226 (2012)

Paramveer S. Dhillon, S. Sathiya Keerthi, Kedar Bellare, Olivier Chapelle, Sundararajan Sellamanickam: Deterministic Annealing for Semi-Supervised Structured Output Learning. Journal of Machine Learning Research - Proceedings Track 22: 299-307 (2012)

Lihong Li, Olivier Chapelle: Open Problem: Regret Bounds for Thompson Sampling. Journal of Machine Learning Research - Proceedings Track 23: 43.1-43.3 (2012)

Olivier Chapelle, Thorsten Joachims, Filip Radlinski, Yisong Yue: Large-scale validation and analysis of interleaved search evaluation. ACM Trans. Inf. Syst. 30(1): 6 (2012)

Zhixiang Eddie Xu, Kilian Q. Weinberger, Olivier Chapelle: The Greedy Miser: Learning under Test-time Budgets. ICML 2012

Umut Ozertem, Olivier Chapelle, Pinar Donmez, Emre Velipasaoglu: Learning to suggest: a machine learning framework for ranking query suggestions. SIGIR 2012: 25-34

Zhixiang Eddie Xu, Kilian Q. Weinberger, Olivier Chapelle: Distance Metric Learning for Kernel Machines. CoRR abs/1208.3422 (2012)

Olivier Chapelle, Shihao Ji, Ciya Liao, Emre Velipasaoglu, Larry Lai, Su-Lin Wu: Intent-based diversification of web search results: metrics and algorithms. Inf. Retr. 14(6): 572-592 (2011)

Olivier Chapelle, Yi Chang: Yahoo! Learning to Rank Challenge Overview. Journal of Machine Learning Research - Proceedings Track 14: 1-24 (2011)

Olivier Chapelle, Yi Chang, Tie-Yan Liu: Future directions in learning to rank. Journal of Machine Learning Research - Proceedings Track 14: 91-100 (2011)

Olivier Chapelle, Pannagadatta K. Shivaswamy, Srinivas Vadrevu, Kilian Q. Weinberger, Ya Zhang, Belle L. Tseng: Boosted multi-task learning. Machine Learning 85(1-2): 149-173 (2011)

Olivier Chapelle, Lihong Li: An Empirical Evaluation of Thompson Sampling. NIPS 2011: 2249-2257

Alekh Agarwal, Olivier Chapelle, Miroslav Dudík, John Langford: A Reliable Effective Terascale Linear Learning System. CoRR abs/1110.4198 (2011)

Olivier Chapelle, S. Sathiya Keerthi: Efficient algorithms for ranking with SVMs. Inf. Retr. 13(3): 201-215 (2010)

Olivier Chapelle, Mingrui Wu: Gradient descent optimization of smoothed information retrieval metrics. Inf. Retr. 13(3): 216-235 (2010)

Bing Bai, Jason Weston, David Grangier, Ronan Collobert, Kunihiko Sadamasa, Yanjun Qi, Olivier Chapelle, Kilian Q. Weinberger: Learning to rank with (a lot of) word features. Inf. Retr. 13(3): 291-314 (2010)

Jacob Abernethy, Olivier Chapelle, Carlos Castillo: Graph regularization methods for Web spam detection. Machine Learning 81(2): 207-225 (2010)

Olivier Chapelle, Pannagadatta K. Shivaswamy, Srinivas Vadrevu, Kilian Q. Weinberger, Ya Zhang, Belle L. Tseng: Multi-task learning for boosting with application to web search ranking. KDD 2010: 1189-1198

Bo Long, Olivier Chapelle, Ya Zhang, Yi Chang, Zhaohui Zheng, Belle L. Tseng: Active learning for ranking through expected loss optimization. SIGIR 2010: 267-274

Yisong Yue, Yue Gao, Olivier Chapelle, Ya Zhang, Thorsten Joachims: Learning more powerful test statistics for click-based retrieval evaluation. SIGIR 2010: 507-514

Berkant Barla Cambazoglu, Hugo Zaragoza, Olivier Chapelle, Jiang Chen, Ciya Liao, Zhaohui Zheng, Jon Degenhardt: Early exit optimizations for additive machine learned ranking systems. WSDM 2010: 411-420

Bing Bai, Jason Weston, David Grangier, Ronan Collobert, Kunihiko Sadamasa, Yanjun Qi, Olivier Chapelle, Kilian Q. Weinberger: Supervised semantic indexing. CIKM 2009: 187-196

Olivier Chapelle, Donald Metlzer, Ya Zhang, Pierre Grinspan: Expected reciprocal rank for graded relevance. CIKM 2009: 621-630

Shihao Ji, Ke Zhou, Ciya Liao, Zhaohui Zheng, Gui-Rong Xue, Olivier Chapelle, Gordon Sun, Hongyuan Zha: Global ranking by exploiting user clicks. SIGIR 2009: 35-42

Olivier Chapelle, Ya Zhang: A dynamic bayesian network click model for web search ranking. WWW 2009: 1-10

Olivier Chapelle, Vikas Sindhwani, S. Sathiya Keerthi: Optimization Techniques for Semi-Supervised Support Vector Machines. Journal of Machine Learning Research 9: 203-233 (2008)

Paul N. Bennett, Ben Carterette, Olivier Chapelle, Thorsten Joachims: Beyond binary relevance: preferences, diversity, and set-level judgments. SIGIR Forum 42(2): 53-58 (2008)

Jacob Abernethy, Olivier Chapelle, Carlos Castillo: Web spam identification through content and hyperlinks. AIRWeb 2008: 41-44

Olivier Chapelle, Chuong B. Do, Quoc V. Le, Alexander J. Smola, Choon Hui Teo: Tighter Bounds for Structured Estimation. NIPS 2008: 281-288

Kilian Q. Weinberger, Olivier Chapelle: Large Margin Taxonomy Embedding for Document Categorization. NIPS 2008: 1737-1744

Peter V. Gehler, Olivier Chapelle: Deterministic Annealing for Multiple-Instance Learning. Journal of Machine Learning Research - Proceedings Track 2: 123-130 (2007)

Olivier Chapelle: Training a Support Vector Machine in the Primal. Neural Computation 19(5): 1155-1178 (2007)

Fabian H. Sinz, Olivier Chapelle, Alekh Agarwal, Bernhard Schölkopf: An Analysis of Inference with the Universum. NIPS 2007

Christian Walder, Olivier Chapelle: Learning with Transformation Invariant Kernels. NIPS 2007

Zhaohui Zheng, Hongyuan Zha, Tong Zhang, Olivier Chapelle, Keke Chen, Gordon Sun: A General Boosting Method and its Application to Learning Ranking Functions for Web Search. NIPS 2007

Christian Walder, Bernhard Schölkopf, Olivier Chapelle: Implicit Surface Modelling with a Globally Regularised Basis of Compact Support. Comput. Graph. Forum 25(3): 635-644 (2006)

S. Sathiya Keerthi, Olivier Chapelle, Dennis DeCoste: Building Support Vector Machines with Reduced Classifier Complexity. Journal of Machine Learning Research 7: 1493-1515 (2006)

Olivier Chapelle, Mingmin Chi, Alexander Zien: A continuation method for semi-supervised SVMs. ICML 2006: 185-192

Vikas Sindhwani, S. Sathiya Keerthi, Olivier Chapelle: Deterministic annealing for semi-supervised kernel machines. ICML 2006: 841-848

Olivier Chapelle, Vikas Sindhwani, S. Sathiya Keerthi: Branch and Bound for Semi-Supervised Support Vector Machines. NIPS 2006: 217-224

Christian Walder, Bernhard Schölkopf, Olivier Chapelle: Implicit Surfaces with Globally Regularised and Compactly Supported Basis Functions. NIPS 2006: 273-280

S. Sathiya Keerthi, Vikas Sindhwani, Olivier Chapelle: An Efficient Method for Gradient-Based Adaptation of Hyperparameters in SVM Models. NIPS 2006: 673-680

Adam Kowalczyk, Olivier Chapelle: An Analysis of the Anti-learning Phenomenon for the Class Symmetric Polyhedron. ALT 2005: 78-91

Christian Walder, Olivier Chapelle, Bernhard Schölkopf: Implicit surface modelling as an eigenvalue problem. ICML 2005: 936-939

Gavin C. Cawley, Nicola L. C. Talbot, Olivier Chapelle: Estimating Predictive Variances with Kernel Ridge Regression. MLCW 2005: 56-77

Mark Everingham, Andrew Zisserman, Christopher K. I. Williams, Luc J. Van Gool, Moray Allan, Christopher M. Bishop, Olivier Chapelle, Navneet Dalal, Thomas Deselaers, Gyuri Dorkó, Stefan Duffner, Jan Eichhorn, Jason D. R. Farquhar, Mario Fritz, Christophe Garcia, Thomas L. Griffiths, Frédéric Jurie, Daniel Keysers, Markus Koskela, Jorma Laaksonen, Diane Larlus, Bastian Leibe, Hongying Meng, Hermann Ney, Bernt Schiele, Cordelia Schmid, Edgar Seemann, John Shawe-Taylor, Amos J. Storkey, Sándor Szedmák, Bill Triggs, Ilkay Ulusoy, Ville Viitaniemi, Jianguo Zhang: The 2005 PASCAL Visual Object Classes Challenge. MLCW 2005: 117-176

Holger Fröhlich, Olivier Chapelle, Bernhard Schölkopf: Feature Selection for Support Vector Machines Using Genetic Algorithms. International Journal on Artificial Intelligence Tools 13(4): 791-800 (2004)

Olivier Chapelle, Zaïd Harchaoui: A Machine Learning Approach to Conjoint Analysis. NIPS 2004

Jason Weston, Fernando Pérez-Cruz, Olivier Bousquet, Olivier Chapelle, André Elisseeff, Bernhard Schölkopf: Feature selection and transduction for prediction of molecular bioactivity for drug design. Bioinformatics 19(6): 764-771 (2003)

Holger Fröhlich, Olivier Chapelle, Bernhard Schölkopf: Feature Selection for Support Vector Machines by Means of Genetic Algorithms. ICTAI 2003: 142-148

Olivier Bousquet, Olivier Chapelle, Matthias Hein: Measure Based Regularization. NIPS 2003

Olivier Chapelle, Vladimir Vapnik, Olivier Bousquet, Sayan Mukherjee: Choosing Multiple Parameters for Support Vector Machines. Machine Learning 46(1-3): 131-159 (2002)

Olivier Chapelle, Vladimir Vapnik, Yoshua Bengio: Model Selection for Small Sample Regression. Machine Learning 48(1-3): 9-23 (2002)

Olivier Chapelle, Jason Weston, Bernhard Schölkopf: Cluster Kernels for Semi-Supervised Learning. NIPS 2002: 585-592

Jason Weston, Olivier Chapelle, André Elisseeff, Bernhard Schölkopf, Vladimir Vapnik: Kernel Dependency Estimation. NIPS 2002: 873-880

Olivier Chapelle, Bernhard Schölkopf: Incorporating Invariances in Non-Linear Support Vector Machines. NIPS 2001: 609-616

Vladimir Vapnik, Olivier Chapelle: Bounds on Error Expectation for Support Vector Machines. Neural Computation 12(9): 2013-2036 (2000)

Olivier Chapelle, Jason Weston, Léon Bottou, Vladimir Vapnik: Vicinal Risk Minimization. NIPS 2000: 416-422

Jason Weston, Sayan Mukherjee, Olivier Chapelle, Massimiliano Pontil, Tomaso Poggio, Vladimir Vapnik: Feature Selection for SVMs. NIPS 2000: 668-674

Olivier Chapelle, Patrick Haffner, Vladimir Vapnik: Support vector machines for histogram-based image classification. IEEE Transactions on Neural Networks 10(5): 1055-1064 (1999)

Olivier Chapelle, Vladimir Vapnik: Model Selection for Support Vector Machines. NIPS 1999: 230-236

Olivier Chapelle, Vladimir Vapnik, Jason Weston: Transductive Inference for Estimating Values of Functions. NIPS 1999: 421-427