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2010 – 2019
- 2017
[c48]Flavian Vasile, Damien Lefortier, Olivier Chapelle:
Cost-sensitive Learning for Utility Optimization in Online Advertising Auctions. ADKDD@KDD 2017: 8:1-8:6- [c47]Yuchin Juan, Damien Lefortier, Olivier Chapelle:
Field-aware Factorization Machines in a Real-world Online Advertising System. WWW (Companion Volume) 2017: 680-688 - [i3]Yuchin Juan, Damien Lefortier, Olivier Chapelle:
Field-aware Factorization Machines in a Real-world Online Advertising System. CoRR abs/1701.04099 (2017) - 2015
- [j22]Bo Long, Jiang Bian, Olivier Chapelle, Ya Zhang
, Yoshiyuki Inagaki, Yi Chang:
Active Learning for Ranking through Expected Loss Optimization. IEEE Trans. Knowl. Data Eng. 27(5): 1180-1191 (2015) - [c46]Olivier Chapelle:
Offline Evaluation of Response Prediction in Online Advertising Auctions. WWW (Companion Volume) 2015: 919-922 - 2014
- [j21]Alekh Agarwal, Olivier Chapelle, Miroslav Dudík, John Langford:
A reliable effective terascale linear learning system. J. Mach. Learn. Res. 15(1): 1111-1133 (2014) - [j20]Zhixiang Eddie Xu, Matt J. Kusner, Kilian Q. Weinberger, Minmin Chen, Olivier Chapelle:
Classifier cascades and trees for minimizing feature evaluation cost. J. Mach. Learn. Res. 15(1): 2113-2144 (2014) - [j19]Olivier Chapelle, Eren Manavoglu, Rómer Rosales:
Simple and Scalable Response Prediction for Display Advertising. ACM Trans. Intell. Syst. Technol. 5(4): 61:1-61:34 (2014) - [c45]Olivier Chapelle:
Modeling delayed feedback in display advertising. KDD 2014: 1097-1105 - 2012
- [j18]Olivier Chapelle, Thorsten Joachims, Filip Radlinski, Yisong Yue:
Large-scale validation and analysis of interleaved search evaluation. ACM Trans. Inf. Syst. 30(1): 6:1-6:41 (2012) - [c44]Zhixiang Eddie Xu, Kilian Q. Weinberger, Olivier Chapelle:
The Greedy Miser: Learning under Test-time Budgets. ICML 2012 - [c43]Umut Ozertem, Olivier Chapelle, Pinar Donmez, Emre Velipasaoglu:
Learning to suggest: a machine learning framework for ranking query suggestions. SIGIR 2012: 25-34 - [c42]Lihong Li, Olivier Chapelle:
Open Problem: Regret Bounds for Thompson Sampling. COLT 2012: 43.1-43.3 - [c41]Minmin Chen, Zhixiang Eddie Xu, Kilian Q. Weinberger, Olivier Chapelle, Dor Kedem:
Classifier Cascade for Minimizing Feature Evaluation Cost. AISTATS 2012: 218-226 - [c40]Paramveer S. Dhillon, S. Sathiya Keerthi, Kedar Bellare, Olivier Chapelle, Sundararajan Sellamanickam:
Deterministic Annealing for Semi-Supervised Structured Output Learning. AISTATS 2012: 299-307 - [i2]Zhixiang Eddie Xu, Kilian Q. Weinberger, Olivier Chapelle:
Distance Metric Learning for Kernel Machines. CoRR abs/1208.3422 (2012) - 2011
- [j17]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) - [j16]Olivier Chapelle, Pannagadatta K. Shivaswamy, Srinivas Vadrevu, Kilian Q. Weinberger, Ya Zhang, Belle L. Tseng:
Boosted multi-task learning. Mach. Learn. 85(1-2): 149-173 (2011) - [c39]Olivier Chapelle, Lihong Li:
An Empirical Evaluation of Thompson Sampling. NIPS 2011: 2249-2257 - [c38]Olivier Chapelle, Yi Chang:
Yahoo! Learning to Rank Challenge Overview. Yahoo! Learning to Rank Challenge 2011: 1-24 - [c37]Olivier Chapelle, Yi Chang, Tie-Yan Liu:
Future directions in learning to rank. Yahoo! Learning to Rank Challenge 2011: 91-100 - [e2]Olivier Chapelle, Yi Chang, Tie-Yan Liu:
Proceedings of the Yahoo! Learning to Rank Challenge, held at ICML 2010, Haifa, Israel, June 25, 2010. JMLR Proceedings 14, JMLR.org 2011 [contents] - [i1]Alekh Agarwal, Olivier Chapelle, Miroslav Dudík, John Langford:
A Reliable Effective Terascale Linear Learning System. CoRR abs/1110.4198 (2011) - 2010
- [j15]Olivier Chapelle, S. Sathiya Keerthi:
Efficient algorithms for ranking with SVMs. Inf. Retr. 13(3): 201-215 (2010) - [j14]Olivier Chapelle, Mingrui Wu:
Gradient descent optimization of smoothed information retrieval metrics. Inf. Retr. 13(3): 216-235 (2010) - [j13]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) - [j12]Jacob D. Abernethy, Olivier Chapelle, Carlos Castillo:
Graph regularization methods for Web spam detection. Mach. Learn. 81(2): 207-225 (2010) - [c36]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 - [c35]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 - [c34]Yisong Yue, Yue Gao, Olivier Chapelle, Ya Zhang, Thorsten Joachims:
Learning more powerful test statistics for click-based retrieval evaluation. SIGIR 2010: 507-514 - [c33]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
2000 – 2009
- 2009
- [c32]Bing Bai, Jason Weston, David Grangier, Ronan Collobert, Kunihiko Sadamasa, Yanjun Qi, Olivier Chapelle, Kilian Q. Weinberger:
Supervised semantic indexing. CIKM 2009: 187-196 - [c31]Olivier Chapelle, Donald Metlzer, Ya Zhang, Pierre Grinspan:
Expected reciprocal rank for graded relevance. CIKM 2009: 621-630 - [c30]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 - [c29]Olivier Chapelle, Ya Zhang:
A dynamic bayesian network click model for web search ranking. WWW 2009: 1-10 - 2008
- [j11]Olivier Chapelle, Vikas Sindhwani, S. Sathiya Keerthi:
Optimization Techniques for Semi-Supervised Support Vector Machines. J. Mach. Learn. Res. 9: 203-233 (2008) - [j10]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) - [c28]Jacob D. Abernethy, Olivier Chapelle, Carlos Castillo:
Web spam identification through content and hyperlinks. AIRWeb 2008: 41-44 - [c27]Olivier Chapelle, Chuong B. Do, Quoc V. Le, Alexander J. Smola, Choon Hui Teo:
Tighter Bounds for Structured Estimation. NIPS 2008: 281-288 - [c26]Kilian Q. Weinberger, Olivier Chapelle:
Large Margin Taxonomy Embedding for Document Categorization. NIPS 2008: 1737-1744 - 2007
- [j9]Olivier Chapelle:
Training a Support Vector Machine in the Primal. Neural Comput. 19(5): 1155-1178 (2007) - [c25]Fabian H. Sinz, Olivier Chapelle, Alekh Agarwal, Bernhard Schölkopf:
An Analysis of Inference with the Universum. NIPS 2007: 1369-1376 - [c24]Christian Walder, Olivier Chapelle:
Learning with Transformation Invariant Kernels. NIPS 2007: 1561-1568 - [c23]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: 1697-1704 - [c22]Peter V. Gehler, Olivier Chapelle:
Deterministic Annealing for Multiple-Instance Learning. AISTATS 2007: 123-130 - 2006
- [j8]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) - [j7]S. Sathiya Keerthi, Olivier Chapelle, Dennis DeCoste:
Building Support Vector Machines with Reduced Classifier Complexity. J. Mach. Learn. Res. 7: 1493-1515 (2006) - [c21]Olivier Chapelle, Mingmin Chi, Alexander Zien:
A continuation method for semi-supervised SVMs. ICML 2006: 185-192 - [c20]Vikas Sindhwani, S. Sathiya Keerthi, Olivier Chapelle:
Deterministic annealing for semi-supervised kernel machines. ICML 2006: 841-848 - [c19]Olivier Chapelle, Vikas Sindhwani, S. Sathiya Keerthi:
Branch and Bound for Semi-Supervised Support Vector Machines. NIPS 2006: 217-224 - [c18]Christian Walder, Bernhard Schölkopf, Olivier Chapelle:
Implicit Surfaces with Globally Regularised and Compactly Supported Basis Functions. NIPS 2006: 273-280 - [c17]S. Sathiya Keerthi, Vikas Sindhwani, Olivier Chapelle:
An Efficient Method for Gradient-Based Adaptation of Hyperparameters in SVM Models. NIPS 2006: 673-680 - [p5]Olivier Chapelle, Bernhard Schölkopf, Alexander Zien:
Introduction to Semi-Supervised Learning. Semi-Supervised Learning 2006: 1-12 - [p4]Olivier Chapelle, Bernhard Schölkopf, Alexander Zien:
Analysis of Benchmarks. Semi-Supervised Learning 2006: 376-393 - [p3]Olivier Chapelle, Bernhard Schölkopf, Alexander Zien:
A Discussion of Semi-Supervised Learning and Transduction. Semi-Supervised Learning 2006: 473-478 - [p2]Thomas Navin Lal, Olivier Chapelle, Jason Weston, André Elisseeff:
Embedded Methods. Feature Extraction 2006: 137-165 - [p1]Thomas Navin Lal, Olivier Chapelle, Bernhard Schölkopf:
Combining a Filter Method with SVMs. Feature Extraction 2006: 439-445 - [e1]Olivier Chapelle, Bernhard Schölkopf, Alexander Zien:
Semi-Supervised Learning. The MIT Press 2006, ISBN 9780262033589 [contents] - 2005
- [c16]Olivier Chapelle:
Active Learning for Parzen Window Classifier. AISTATS 2005: 49-56 - [c15]Olivier Chapelle, Alexander Zien:
Semi-Supervised Classification by Low Density Separation. AISTATS 2005: 57-64 - [c14]Adam Kowalczyk, Olivier Chapelle:
An Analysis of the Anti-learning Phenomenon for the Class Symmetric Polyhedron. ALT 2005: 78-91 - [c13]Christian Walder, Olivier Chapelle, Bernhard Schölkopf:
Implicit surface modelling as an eigenvalue problem. ICML 2005: 936-939 - [c12]Gavin C. Cawley, Nicola L. C. Talbot, Olivier Chapelle:
Estimating Predictive Variances with Kernel Ridge Regression. MLCW 2005: 56-77 - [c11]Mark Everingham, Andrew Zisserman, Christopher K. I. Williams, Luc 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, Tom 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 - 2004
- [j6]Holger Fröhlich, Olivier Chapelle, Bernhard Schölkopf:
Feature Selection for Support Vector Machines Using Genetic Algorithms. Int. J. Artif. Intell. Tools 13(4): 791-800 (2004) - [c10]Olivier Chapelle, Zaïd Harchaoui:
A Machine Learning Approach to Conjoint Analysis. NIPS 2004: 257-264 - 2003
- [j5]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. Bioinform. 19(6): 764-771 (2003) - [c9]Holger Fröhlich, Olivier Chapelle, Bernhard Schölkopf:
Feature Selection for Support Vector Machines by Means of Genetic Algorithms. ICTAI 2003: 142-148 - [c8]Olivier Bousquet, Olivier Chapelle, Matthias Hein:
Measure Based Regularization. NIPS 2003: 1221-1228 - 2002
- [j4]Olivier Chapelle, Vladimir Vapnik, Olivier Bousquet, Sayan Mukherjee:
Choosing Multiple Parameters for Support Vector Machines. Mach. Learn. 46(1-3): 131-159 (2002) - [j3]Olivier Chapelle, Vladimir Vapnik, Yoshua Bengio:
Model Selection for Small Sample Regression. Mach. Learn. 48(1-3): 9-23 (2002) - [c7]Olivier Chapelle, Jason Weston, Bernhard Schölkopf:
Cluster Kernels for Semi-Supervised Learning. NIPS 2002: 585-592 - [c6]Jason Weston, Olivier Chapelle, André Elisseeff, Bernhard Schölkopf, Vladimir Vapnik:
Kernel Dependency Estimation. NIPS 2002: 873-880 - 2001
- [c5]Olivier Chapelle, Bernhard Schölkopf:
Incorporating Invariances in Non-Linear Support Vector Machines. NIPS 2001: 609-616 - 2000
- [j2]Vladimir Vapnik, Olivier Chapelle:
Bounds on Error Expectation for Support Vector Machines. Neural Comput. 12(9): 2013-2036 (2000) - [c4]Olivier Chapelle, Jason Weston, Léon Bottou, Vladimir Vapnik:
Vicinal Risk Minimization. NIPS 2000: 416-422 - [c3]Jason Weston, Sayan Mukherjee, Olivier Chapelle, Massimiliano Pontil, Tomaso A. Poggio, Vladimir Vapnik:
Feature Selection for SVMs. NIPS 2000: 668-674
1990 – 1999
- 1999
- [j1]Olivier Chapelle, Patrick Haffner, Vladimir Vapnik:
Support vector machines for histogram-based image classification. IEEE Trans. Neural Networks 10(5): 1055-1064 (1999) - [c2]Olivier Chapelle, Vladimir Vapnik:
Model Selection for Support Vector Machines. NIPS 1999: 230-236 - [c1]Olivier Chapelle, Vladimir Vapnik, Jason Weston:
Transductive Inference for Estimating Values of Functions. NIPS 1999: 421-427
Coauthor Index
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