2009 |
35 | EE | Olivier Chapelle,
Ya Zhang:
A dynamic bayesian network click model for web search ranking.
WWW 2009: 1-10 |
2008 |
34 | EE | Jacob Abernethy,
Olivier Chapelle,
Carlos Castillo:
Web spam identification through content and hyperlinks.
AIRWeb 2008: 41-44 |
33 | EE | Kilian Q. Weinberger,
Olivier Chapelle:
Large Margin Taxonomy Embedding for Document Categorization.
NIPS 2008: 1737-1744 |
32 | EE | Olivier Chapelle,
Chuong B. Do,
Quoc V. Le,
Alexander J. Smola,
Choon Hui Teo:
Tighter Bounds for Structured Estimation.
NIPS 2008: 281-288 |
2007 |
31 | EE | 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 |
30 | EE | Fabian H. Sinz,
Olivier Chapelle,
Alekh Agarwal,
Bernhard Schölkopf:
An Analysis of Inference with the Universum.
NIPS 2007 |
29 | EE | Christian Walder,
Olivier Chapelle:
Learning with Transformation Invariant Kernels.
NIPS 2007 |
28 | EE | Olivier Chapelle:
Training a Support Vector Machine in the Primal.
Neural Computation 19(5): 1155-1178 (2007) |
2006 |
27 | EE | Olivier Chapelle,
Mingmin Chi,
Alexander Zien:
A continuation method for semi-supervised SVMs.
ICML 2006: 185-192 |
26 | EE | Vikas Sindhwani,
S. Sathiya Keerthi,
Olivier Chapelle:
Deterministic annealing for semi-supervised kernel machines.
ICML 2006: 841-848 |
25 | EE | Olivier Chapelle,
Vikas Sindhwani,
S. Sathiya Keerthi:
Branch and Bound for Semi-Supervised Support Vector Machines.
NIPS 2006: 217-224 |
24 | EE | Christian Walder,
Bernhard Schölkopf,
Olivier Chapelle:
Implicit Surfaces with Globally Regularised and Compactly Supported Basis Functions.
NIPS 2006: 273-280 |
23 | EE | S. Sathiya Keerthi,
Vikas Sindhwani,
Olivier Chapelle:
An Efficient Method for Gradient-Based Adaptation of Hyperparameters in SVM Models.
NIPS 2006: 673-680 |
22 | EE | 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) |
21 | EE | S. Sathiya Keerthi,
Olivier Chapelle,
Dennis DeCoste:
Building Support Vector Machines with Reduced Classifier Complexity.
Journal of Machine Learning Research 7: 1493-1515 (2006) |
2005 |
20 | EE | Adam Kowalczyk,
Olivier Chapelle:
An Analysis of the Anti-learning Phenomenon for the Class Symmetric Polyhedron.
ALT 2005: 78-91 |
19 | EE | Christian Walder,
Olivier Chapelle,
Bernhard Schölkopf:
Implicit surface modelling as an eigenvalue problem.
ICML 2005: 936-939 |
18 | EE | 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,
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 |
17 | EE | Gavin C. Cawley,
Nicola L. C. Talbot,
Olivier Chapelle:
Estimating Predictive Variances with Kernel Ridge Regression.
MLCW 2005: 56-77 |
2004 |
16 | EE | Olivier Chapelle,
Zaïd Harchaoui:
A Machine Learning Approach to Conjoint Analysis.
NIPS 2004 |
15 | EE | 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) |
2003 |
14 | EE | Holger Fröhlich,
Olivier Chapelle,
Bernhard Schölkopf:
Feature Selection for Support Vector Machines by Means of Genetic Algorithms.
ICTAI 2003: 142-148 |
13 | EE | Olivier Bousquet,
Olivier Chapelle,
Matthias Hein:
Measure Based Regularization.
NIPS 2003 |
12 | | 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) |
2002 |
11 | EE | Olivier Chapelle,
Jason Weston,
Bernhard Schölkopf:
Cluster Kernels for Semi-Supervised Learning.
NIPS 2002: 585-592 |
10 | EE | Jason Weston,
Olivier Chapelle,
André Elisseeff,
Bernhard Schölkopf,
Vladimir Vapnik:
Kernel Dependency Estimation.
NIPS 2002: 873-880 |
9 | | Olivier Chapelle,
Vladimir Vapnik,
Olivier Bousquet,
Sayan Mukherjee:
Choosing Multiple Parameters for Support Vector Machines.
Machine Learning 46(1-3): 131-159 (2002) |
8 | | Olivier Chapelle,
Vladimir Vapnik,
Yoshua Bengio:
Model Selection for Small Sample Regression.
Machine Learning 48(1-3): 9-23 (2002) |
2001 |
7 | EE | Olivier Chapelle,
Bernhard Schölkopf:
Incorporating Invariances in Non-Linear Support Vector Machines.
NIPS 2001: 609-616 |
2000 |
6 | | Olivier Chapelle,
Jason Weston,
Léon Bottou,
Vladimir Vapnik:
Vicinal Risk Minimization.
NIPS 2000: 416-422 |
5 | | Jason Weston,
Sayan Mukherjee,
Olivier Chapelle,
Massimiliano Pontil,
Tomaso Poggio,
Vladimir Vapnik:
Feature Selection for SVMs.
NIPS 2000: 668-674 |
4 | | Vladimir Vapnik,
Olivier Chapelle:
Bounds on Error Expectation for Support Vector Machines.
Neural Computation 12(9): 2013-2036 (2000) |
1999 |
3 | EE | Olivier Chapelle,
Vladimir Vapnik:
Model Selection for Support Vector Machines.
NIPS 1999: 230-236 |
2 | EE | Olivier Chapelle,
Vladimir Vapnik,
Jason Weston:
Transductive Inference for Estimating Values of Functions.
NIPS 1999: 421-427 |
1 | EE | Olivier Chapelle,
Patrick Haffner,
Vladimir Vapnik:
Support vector machines for histogram-based image classification.
IEEE Transactions on Neural Networks 10(5): 1055-1064 (1999) |