PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

EPrints submitted by Gilles Blanchard

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Number of EPrints submitted by this user: 37

Oracle bounds and exact algorithm for dyadic classification trees
Gilles Blanchard, Christin Schaefer and Yves Rozenholc
In: COLT 2004, 1-4 Jul. 2004, Banff, Canada.

Statistical Properties of Kernel Principal Component Analysis
Olivier Bousquet, Laurent Zwald and Gilles Blanchard
In: 17th. Conference on Learning Theory (COLT 2004), 1-4 July 2004, Banff, Canada.

Different paradigms for choosing sequential reweighting algorithms
Gilles Blanchard
Neural Computation Number 16, pp. 811-836, 2004.

Kernel Projection Machine: a New Tool for Pattern Recognition
Gilles Blanchard, Pascal Massart, Regis Vert and Laurent Zwald
In: NIPS 2004, 13-16 Dec 2004, Vancouver, Canada.

BCI competition 2003 -- data set IIa: Spatial patterns of self-controlled brain rhythm modulations
Gilles Blanchard and Benjamin Blankertz
IEEE Transactions in Biomedical Engineering Volume 51, Number 6, pp. 1062-1066, 2004.

Hierarchical Testing Designs for Pattern Recognition
Gilles Blanchard and Donald Geman
Annals of Statistics Volume 33, Number 3, pp. 1155-1202, 2005.

Optimal Dyadic Decision Trees
Gilles Blanchard, Christin Schaefer, Yves Rozenholc and Klaus-Robert Müller
Machine Learning Volume 66, Number 2-3, pp. 209-242, 2007.

Statistical Properties of Kernel Principal Component Analysis
Gilles Blanchard, Olivier Bousquet and Laurent Zwald
Machine Learning Volume 66, Number 2-3, pp. 259-294, 2007.

In Search of Non-Gaussian Components of a High-Dimensional Distribution
Gilles Blanchard, Motoaki Kawanabe, Masashi Sugiyama, Vladimir Spokoiny and Klaus-Robert Müller
Journal of Machine Learning Research Volume 7, pp. 247-282, 2006.

On the Convergence of Eigenspaces in Kernel Principal Component Analysis
Laurent Zwald and Gilles Blanchard
In: NIPS 2005, 5-8 Dec 2005, Vancouver.

Pattern Recognition from One Example by Chopping
François Fleuret and Gilles Blanchard
In: NIPS 2005, 5-8 Dec 2005, Vancouver, Canada.

Non-Gaussian Component Analysis: a Semiparametric Framework for Linear Dimension Reduction
Gilles Blanchard, Motoaki Kawanabe, Masashi Sugiyama, Vladimir Spokoiny and Klaus-Robert Müller
In: NIPS 2005, 5-8 Dec 2005, Vancouver, Canada.

An accelerated algorithm for MCMC Bayesian decision tree sampling
Gilles Blanchard
In: Workshop Ensemble Methods, 4-5 march 2005.

Discussion of V.Koltchinskii's 2004 IMS Medallion Lecture paper, "Local Rademacher complexities and oracle inequalities in risk minimization"
Gilles Blanchard and Pascal Massart
Annals of Statistics Volume 34, Number 6, 2006.

Occam's hammer
Gilles Blanchard and François Fleuret
In: 20th conference on Learning Theory (COLT 2007), 13-15 June 2007, San Diego, CA, USA.

Finite dimensional projection for classification and statistical learning
Gilles Blanchard and Laurent Zwald
IEEE transactions on information theory Volume 54, Number 9, pp. 4169-4182, 2008. ISSN 0018-9448

Statistical Performance of Support Vector Machines
Gilles Blanchard, Olivier Bousquet and Pascal Massart
Annals of Statistics Volume 36, Number 2, pp. 489-531, 2008. ISSN 00905364

Obtaining the best linear unbiased estimator of noisy signals by non-gaussian component analysis
Motoaki Kawanabe, Gilles Blanchard, Masashi Sugiyama, Vladimir Spokoiny and Klaus-Robert Müller
In: ICASSP 06, 15-19 May 2006, Toulouse, France.

A novel dimension reduction procedure for searching non-gaussian subspaces.
Motoaki Kawanabe, Gilles Blanchard, Masashi Sugiyama, Vladimir Spokoiny and Klaus-Robert Müller
In: ICA 2006, 5-8 march 2006, Charleston, USA.

A new algorithm of non-Gaussian component analysis with radial kernel functions
Motoaki Kawanabe, Gilles Blanchard, Masahi Sugiyama and Klaus-Robert Müller
Annals of the Institute of Statistical Mathematics Volume 59, Number 1, pp. 57-75, 2007.

Resampling-based confidence regions and multiple tests for a correlated random vector
Sylvain Arlot, Gilles Blanchard and Etienne Roquain
In: 20th conference on Learning Theory (COLT 2007), 13-15 June 2007, San Diego, CA, USA.

Some nonasymptotic results on resampling in high dimension, I: Confidence regions
Sylvain Arlot, Gilles Blanchard and Etienne Roquain
Annals of Statistics Volume 38, Number 1, pp. 51-82, 2010. ISSN 00905364

Self-consistent multiple testing procedures
Gilles Blanchard and Étienne Roquain
2008.

Two simple sufficient conditions for FDR control
Gilles Blanchard and Etienne Roquain
Electronic Journal of Statistics Volume 2, pp. 963-992, 2008. ISSN 1935-7524

Approximating the Best Linear Unbiased Estimator of Non-Gaussian Signals with Gaussian Noise
Masashi Sugiyama, Motoaki Kawanabe, Gilles Blanchard and Klaus-Robert Müller
IEICE Transactions on Information and Systems Volume E91-D, Number 5, pp. 1577-1580, 2008. ISSN 0916-8532 (print) 1745-1361 (online)

Novelty detection: Unlabeled data definitely help
Clayton Scott and Gilles Blanchard
In: AISTATS 2009, 16-18 Apr 2009, Clearwater beach, USA.

Some nonasymptotic results on resampling in high dimension, II: Multiple tests
Sylvain Arlot, Gilles Blanchard and Etienne Roquain
Annals of Statistics Volume 38, Number 1, pp. 83-99, 2010. ISSN 00905364

How wrong can we get? A review of machine learning approaches and error bars.
Anton Schwaighofer, Timon Schröter, Sebastian Mika and Gilles Blanchard
Combinatorial Chemistry & High Throughput Screening Volume 12, Number 5, pp. 453-468, 2009. ISSN 1386-2073

Adaptive False Discovery Rate Control under Independence and Dependence
Gilles Blanchard and Etienne Roquain
Journal of Machine Learning Research Volume 10, pp. 2837-2871, 2009. ISSN 1533-7928

Semi-supervised novelty detection
Gilles Blanchard, Gyemin Lee and Clayton Scott
Journal of Machine Learning Research Volume 11, pp. 2973-3009, 2010. ISSN 1533-7928

Optimal Learning Rates for Kernel Conjugate Gradient Regularization
Gilles Blanchard and Nicole Krämer
In: NIPS 2010, 6-9 Dec 2010, Vanouver, Canada.

Kernel Partial Least Squares is Universally Consistent
Gilles Blanchard and Nicole Krämer
In: AISTATS 2010, May 13-15, 2010, Sardinia, Italy.

Conjugate gradient regularization under general smoothness and noise assumptions
Gilles Blanchard and Peter Mathé
Journal of Inverse and Ill-posed Problems Volume 18, Number 6, pp. 701-726, 2010. ISSN 0928-0219

Generalizing from several related classification tasks to a new unlabeled sample
Gilles Blanchard, Gyemin Lee and Clayton Scott
Neural Information Processing Systems (NIPS) 2011.

Testing over a continuum of null hypotheses
Gilles Blanchard, Sylvain Delattre and Étienne Roquain
ArXiv Preprint Number 1110.3599, 2011.

On least favorable configurations for step-up-down tests
Gilles Blanchard, Thorsten Dickhaus, Étienne Roquain and Fanny Villers
ArXiv Preprint Number 1108.5262, 2011.

Discrepancy Principle for Statistical Inverse Problems with Application to Conjugate Gradient Iteration
Gilles Blanchard and Peter Mathé
Preprint, University of Potsdam Number 2011.07, 2011.