Olivier Chapelle

发表

Data cleaning algorithms with applications to micro-array experiments

Jason Weston, Isabelle Guyon, Olivier Chapelle, 2001 .

Introduction to Semi-Supervised Learning

Bernhard Schölkopf, Alexander Zien, Olivier Chapelle, 2006, Semi-Supervised Learning.

A taxonomy of semi-supervised learning algorithms

Olivier Chapelle, O. Chapelle, 2005 .

Embedded Methods

Jason Weston, André Elisseeff, Olivier Chapelle, 2006, Feature Extraction.

A Discussion of Semi-Supervised Learning and Transduction

Bernhard Schölkopf, Alexander Zien, Olivier Chapelle, 2006, Semi-Supervised Learning.

Combining a Filter Method with SVMs

Bernhard Schölkopf, Olivier Chapelle, Thomas Navin Lal, 2006, Feature Extraction.

A dynamic bayesian network click model for web search ranking

Olivier Chapelle, Ya Zhang, O. Chapelle, 2009, WWW '09.

Risks of Semi-Supervised Learning: How Unlabeled Data Can Degrade Performance of Generative Classifiers

Alexander Zien, Olivier Chapelle, Bernhard SchÃ¶lkopf, 2006 .

Large-Scale Algorithms

Alexander Zien, Olivier Chapelle, Bernhard SchÃ¶lkopf, 2006 .

Building Support Vector Machines with Reduced Classifier Complexity

S. Sathiya Keerthi, Dennis DeCoste, Olivier Chapelle, 2006, J. Mach. Learn. Res..

Low-Density Separation

Alexander Zien, Olivier Chapelle, Bernhard SchÃ¶lkopf, 2006 .

Label Propagation and Quadratic Criterion

Alexander Zien, Olivier Chapelle, Bernhard SchÃ¶lkopf, 2006 .

Feature Selection for Support Vector Machines Using Genetic Algorithms

Bernhard Schölkopf, Holger Fröhlich, Olivier Chapelle, 2004, Int. J. Artif. Intell. Tools.

Building SVMs with Reduced Classifier Complexity

Jason Weston, Dennis DeCoste, Léon Bottou, 2007 .

Learning more powerful test statistics for click-based retrieval evaluation

Yue Gao, Thorsten Joachims, Ya Zhang, 2010, SIGIR.

Support Vector Machines: Induction Principle, Adaptive Tuning and Prior Knowledge

Olivier Chapelle, O. Chapelle, 2002 .

Yahoo! Learning to Rank Challenge Overview

Yi Chang, Olivier Chapelle, O. Chapelle, 2010, Yahoo! Learning to Rank Challenge.

Open Problem: Regret Bounds for Thompson Sampling

Lihong Li, Olivier Chapelle, 2012, COLT.

A reliable effective terascale linear learning system

John Langford, Miroslav Dudík, Alekh Agarwal, 2011, J. Mach. Learn. Res..

Offline Evaluation of Response Prediction in Online Advertising Auctions

Olivier Chapelle, O. Chapelle, 2015, WWW.

Web spam identification through content and hyperlinks

Carlos Castillo, Jacob D. Abernethy, Olivier Chapelle, 2008, AIRWeb '08.

Change of Representation

Alexander Zien, Olivier Chapelle, Bernhard SchÃ¶lkopf, 2006 .

Expected reciprocal rank for graded relevance

Olivier Chapelle, Pierre Grinspan, Ya Zhang, 2009, CIKM.

Model Selection for Small Sample Regression

Yoshua Bengio, Olivier Chapelle, Vladimir Vapnik, 2002, Machine Learning.

Learning with Transformation Invariant Kernels

Christian Walder, Olivier Chapelle, O. Chapelle, 2007, NIPS.

Semi-Supervised Learning in Practice

Alexander Zien, Olivier Chapelle, Bernhard SchÃ¶lkopf, 2006 .

Deterministic Annealing for Semi-Supervised Structured Output Learning

S. Sathiya Keerthi, Paramveer S. Dhillon, Sundararajan Sellamanickam, 2012, AISTATS.

Branch and Bound for Semi-Supervised Support Vector Machines

S. Sathiya Keerthi, Vikas Sindhwani, Olivier Chapelle, 2006, NIPS.

Support Vector Machines : principes d'induction, Réglage automatique et connaissances à priori

Olivier Chapelle, O. Chapelle, 2004 .

Deterministic Annealing for Multiple-Instance Learning

Peter V. Gehler, Olivier Chapelle, O. Chapelle, 2007, AISTATS.

Beyond binary relevance: preferences, diversity, and set-level judgments

Ben Carterette, Thorsten Joachims, Paul N. Bennett, 2008, SIGF.

Simple and Scalable Response Prediction for Display Advertising

Rómer Rosales, Olivier Chapelle, Eren Manavoglu, 2014, ACM Trans. Intell. Syst. Technol..

Graph Kernels by Spectral Transforms

Alexander Zien, Olivier Chapelle, Bernhard SchÃ¶lkopf, 2006 .

Semi-Supervised Text Classification Using EM

Alexander Zien, Olivier Chapelle, Bernhard SchÃ¶lkopf, 2006 .

Measure Based Regularization

Matthias Hein, Olivier Chapelle, Olivier Bousquet, 2003, NIPS.

Gaussian Processes and the Null-Category Noise Model

Alexander Zien, Olivier Chapelle, Bernhard SchÃ¶lkopf, 2006 .

An Analysis of Inference with the Universum

Bernhard Schölkopf, Alekh Agarwal, Olivier Chapelle, 2007, NIPS.

Tighter Bounds for Structured Estimation

Alexander J. Smola, Quoc V. Le, Choon Hui Teo, 2008, NIPS.

Global ranking by exploiting user clicks

Hongyuan Zha, Zhaohui Zheng, Gui-Rong Xue, 2009, SIGIR.

Gradient descent optimization of smoothed information retrieval metrics

Mingrui Wu, Olivier Chapelle, O. Chapelle, 2010, Information Retrieval.

Graph-Based Methods

Alexander Zien, Olivier Chapelle, Bernhard SchÃ¶lkopf, 2006 .

The 2005 PASCAL Visual Object Classes Challenge

Cordelia Schmid, Jorma Laaksonen, Luc Van Gool, 2005, MLCW.

Graph regularization methods for Web spam detection

Carlos Castillo, Jacob D. Abernethy, Olivier Chapelle, 2010, Machine Learning.

Transductive Inference for Estimating Values of Functions

Jason Weston, Olivier Chapelle, Vladimir Vapnik, 1999, NIPS.

Cluster Kernels for Semi-Supervised Learning

Bernhard Schölkopf, Jason Weston, Olivier Chapelle, 2002, NIPS.

Early exit optimizations for additive machine learned ranking systems

Berkant Barla Cambazoglu, Zhaohui Zheng, Hugo Zaragoza, 2010, WSDM '10.

Supervised semantic indexing

Yanjun Qi, Jason Weston, Bing Bai, 2009, ECIR.

Modeling delayed feedback in display advertising

Olivier Chapelle, O. Chapelle, 2014, KDD.

Feature Selection for SVMs

Sayan Mukherjee, Jason Weston, Tomaso A. Poggio, 2000, NIPS.

Training a Support Vector Machine in the Primal

Olivier Chapelle, O. Chapelle, 2007, Neural Computation.

Probabilistic Semi-Supervised Clustering with Constraints

Alexander Zien, Olivier Chapelle, Bernhard SchÃ¶lkopf, 2006 .

Training Invariant SVMs Using Selective Sampling

Jason Weston, Dennis DeCoste, Léon Bottou, 2007 .

An Efficient Method for Gradient-Based Adaptation of Hyperparameters in SVM Models

S. Sathiya Keerthi, Vikas Sindhwani, Olivier Chapelle, 2006, NIPS.

Semi-Supervised Learning

Alexander Zien, Olivier Chapelle, Bernhard Schlkopf, 2006 .

Estimating Predictive Variances with Kernel Ridge Regression

Gavin C. Cawley, Nicola L. C. Talbot, Olivier Chapelle, 2005, MLCW.

The Greedy Miser: Learning under Test-time Budgets

Kilian Q. Weinberger, Olivier Chapelle, Zhixiang Eddie Xu, 2012, ICML.

The Geometric Basis of Semi-Supervised Learning

Alexander Zien, Olivier Chapelle, Bernhard SchÃ¶lkopf, 2006 .

Active Learning for Parzen Window Classifier

Olivier Chapelle, O. Chapelle, 2005, AISTATS.

Classifier Cascade for Minimizing Feature Evaluation Cost

Kilian Q. Weinberger, Minmin Chen, Olivier Chapelle, 2012, AISTATS.

Active Learning for Ranking through Expected Loss Optimization

Ya Zhang, Zhaohui Zheng, Yi Chang, 2010, IEEE Transactions on Knowledge and Data Engineering.

Cost-sensitive Learning for Utility Optimization in Online Advertising Auctions

Olivier Chapelle, Flavian Vasile, Damien Lefortier, 2016, ADKDD@KDD.

Implicit Surfaces with Globally Regularised and Compactly Supported Basis Functions

Bernhard Schölkopf, Christian Walder, Olivier Chapelle, 2006, NIPS.

Kernel Dependency Estimation

Bernhard Schölkopf, Jason Weston, André Elisseeff, 2002, NIPS.

Efficient algorithms for ranking with SVMs

S. Sathiya Keerthi, Olivier Chapelle, O. Chapelle, 2010, Information Retrieval.

Analysis of Benchmarks

Bernhard Schölkopf, Alexander Zien, Olivier Chapelle, 2006, Semi-Supervised Learning.

Learning to suggest: a machine learning framework for ranking query suggestions

Umut Ozertem, Emre Velipasaoglu, Pinar Donmez, 2012, SIGIR '12.

Semi-Supervised Learning with Conditional Harmonic Mixing

Alexander Zien, Olivier Chapelle, Bernhard SchÃ¶lkopf, 2006 .

Active Learning for Ranking through Expected Loss Optimization

Ya Zhang, Jiang Bian, Yi Chang, 2015, IEEE Trans. Knowl. Data Eng..

Boosted multi-task learning

Ya Zhang, Kilian Q. Weinberger, Belle L. Tseng, 2010, Machine Learning.

A Machine Learning Approach to Conjoint Analysis

Zaïd Harchaoui, Olivier Chapelle, O. Chapelle, 2004, NIPS.

Semi-Supervised Learning through Principal Directions Estimation

Bernhard Schölkopf, Jason Weston, Olivier Chapelle, 2003, ICML 2003.

Intent-based diversification of web search results: metrics and algorithms

Emre Velipasaoglu, Larry Lai, Ciya Liao, 2011, Information Retrieval.

Large-Scale Kernel Machines (Neural Information Processing)

Jason Weston, Dennis DeCoste, Léon Bottou, 2007 .

Semi-Supervised Classification by Low Density Separation

Alexander Zien, Olivier Chapelle, O. Chapelle, 2005, AISTATS.

Metric-Based Approaches for Semi-Supervised Regression and Classification

Alexander Zien, Olivier Chapelle, Bernhard SchÃ¶lkopf, 2006 .

Fast Kernel Learning with Sparse Inverted Index

Jason Weston, Dennis DeCoste, Léon Bottou, 2007 .

Data-Dependent Regularization

Alexander Zien, Olivier Chapelle, Bernhard SchÃ¶lkopf, 2006 .

Implicit Surface Modelling with a Globally Regularised Basis of Compact Support

Bernhard Schölkopf, Christian Walder, Olivier Chapelle, 2006, Comput. Graph. Forum.

Semi-Supervised Learning (Adaptive Computation and Machine Learning)

Bernhard Schölkopf, Alexander Zien, Olivier Chapelle, 2006 .

Future directions in learning to rank

Tie-Yan Liu, Yi Chang, Olivier Chapelle, 2010, Yahoo! Learning to Rank Challenge.

An Augmented PAC Model for Semi-Supervised Learning

Alexander Zien, Olivier Chapelle, Bernhard SchÃ¶lkopf, 2006 .

Optimization Techniques for Semi-Supervised Support Vector Machines

S. Sathiya Keerthi, Vikas Sindhwani, Olivier Chapelle, 2008, J. Mach. Learn. Res..

A General Boosting Method and its Application to Learning Ranking Functions for Web Search

Hongyuan Zha, Keke Chen, Zhaohui Zheng, 2007, NIPS.

Large-Scale Parallel SVM Implementation

Jason Weston, Dennis DeCoste, Léon Bottou, 2007 .

Classifier cascades and trees for minimizing feature evaluation cost

Matt J. Kusner, Kilian Q. Weinberger, Minmin Chen, 2014, J. Mach. Learn. Res..

Multi-task learning for boosting with application to web search ranking

Ya Zhang, Kilian Q. Weinberger, Belle L. Tseng, 2010, KDD.

Scaling Learning Algorithms toward AI

Jason Weston, Dennis DeCoste, Léon Bottou, 2007 .

Adaptive Parameters for Entity Recognition with Perceptron HMMs

Massimiliano Ciaramita, Olivier Chapelle, O. Chapelle, 2010 .

Incorporating Invariances in Non-Linear Support Vector Machines

Bernhard Schölkopf, Olivier Chapelle, B. Schölkopf, 2001, NIPS.

Distance Metric Learning for Kernel Machines pdf

Kilian Q. Weinberger, Olivier Chapelle, Zhixiang Eddie Xu, 2012, ArXiv.

Learning to rank with (a lot of) word features

Yanjun Qi, Jason Weston, Bing Bai, 2010, Information Retrieval.

Field-aware Factorization Machines in a Real-world Online Advertising System

Olivier Chapelle, Damien Lefortier, Yuchin Juan, 2017, WWW.

Large-scale validation and analysis of interleaved search evaluation

Filip Radlinski, Thorsten Joachims, Yisong Yue, 2012, TOIS.

An Analysis of the Anti-learning Phenomenon for the Class Symmetric Polyhedron

Adam Kowalczyk, Olivier Chapelle, O. Chapelle, 2005, ALT.

An Empirical Evaluation of Thompson Sampling

Lihong Li, Olivier Chapelle, O. Chapelle, 2011, NIPS.

A Taxonomy for Semi-Supervised Learning Methods

Alexander Zien, Olivier Chapelle, Bernhard SchÃ¶lkopf, 2006 .

The Improved Fast Gauss Transform with Applications to Machine Learning

Jason Weston, Dennis DeCoste, Léon Bottou, 2007 .

KDD Cup 2001 data analysis: prediction of molecular bioactivity for drug Design-Binding to Thrombin

Bernhard Schölkopf, Jason Weston, André Elisseeff, 2001, Knowledge Discovery and Data Mining.

Transductive Support Vector Machines

Alexander Zien, Olivier Chapelle, Bernhard SchÃ¶lkopf, 2006 .

Large Margin Taxonomy Embedding for Document Categorization

Kilian Q. Weinberger, Olivier Chapelle, O. Chapelle, 2008, NIPS.

Model Selection for Support Vector Machines

Olivier Chapelle, Vladimir Vapnik, O. Chapelle, 1999, NIPS.

Deterministic annealing for semi-supervised kernel machines

S. Sathiya Keerthi, Vikas Sindhwani, Olivier Chapelle, 2006, ICML.

Implicit surface modelling as an eigenvalue problem

Bernhard Schölkopf, Christian Walder, Olivier Chapelle, 2005, ICML.

A continuation method for semi-supervised SVMs

Alexander Zien, Mingmin Chi, Olivier Chapelle, 2006, ICML.

Vicinal Risk Minimization

Jason Weston, Léon Bottou, Olivier Chapelle, 2000, NIPS.

Support vector machines for histogram-based image classification

Patrick Haffner, Olivier Chapelle, Vladimir Vapnik, 1999, IEEE Trans. Neural Networks.

Choosing Multiple Parameters for Support Vector Machines

Sayan Mukherjee, Olivier Chapelle, Vladimir Vapnik, 2002, Machine Learning.

Transductive Inference and Semi-Supervised Learning

Alexander Zien, Olivier Chapelle, Bernhard SchÃ¶lkopf, 2006 .

Feature selection for support vector machines by means of genetic algorithm

Bernhard Schölkopf, Holger Fröhlich, Olivier Chapelle, 2003, Proceedings. 15th IEEE International Conference on Tools with Artificial Intelligence.

Notation and Symbols

Alexander Zien, Olivier Chapelle, Bernhard SchÃ¶lkopf, 2006 .

Incorporating invariances in nonlinear Support Vector Machines

Bernhard Schölkopf, Olivier Chapelle, B. Schölkopf, 2001, NIPS 2001.

Semi-Supervised Learning Using Semi-Definite Programming

Alexander Zien, Olivier Chapelle, Bernhard SchÃ¶lkopf, 2006 .

Some thoughts about Gaussian Processes

Olivier Chapelle, 2005, NIPS 2005.

Learning to Rank Challenge Future directions in learning to rank

Yi Chang, Olivier Chapelle, 2011 .

A Test Collection of Preference Judgments

Ben Carterette, Paul N. Bennett, Olivier Chapelle, 2017 .