Gilles Blanchard

According to our database1, Gilles Blanchard authored at least 59 papers between 2003 and 2024.

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Bibliography

2024
Estimation of multiple mean vectors in high dimension.
CoRR, 2024

2023
Transductive conformal inference with adaptive scores.
CoRR, 2023

Label Shift Quantification with Robustness Guarantees via Distribution Feature Matching.
Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

Covariance-adaptive best arm identification.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Constant regret for sequence prediction with limited advice.
Proceedings of the International Conference on Algorithmic Learning Theory, 2023

2022
Topologically penalized regression on manifolds.
J. Mach. Learn. Res., 2022

2021
Domain Generalization by Marginal Transfer Learning.
J. Mach. Learn. Res., 2021

Error rate control for classification rules in multiclass mixture models.
CoRR, 2021

Nonasymptotic one-and two-sample tests in high dimension with unknown covariance structure.
CoRR, 2021

Fast rates for prediction with limited expert advice.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

High-Dimensional Multi-Task Averaging and Application to Kernel Mean Embedding.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
Online Orthogonal Matching Pursuit.
CoRR, 2020

Statistical Learning Guarantees for Compressive Clustering and Compressive Mixture Modeling.
CoRR, 2020

2019
Decontamination of Mutual Contamination Models.
J. Mach. Learn. Res., 2019

Volume Doubling Condition and a Local Poincaré Inequality on Unweighted Random Geometric Graphs.
CoRR, 2019

Efficient Regularized Piecewise-Linear Regression Trees.
CoRR, 2019

Restless dependent bandits with fading memory.
CoRR, 2019

A minimax near-optimal algorithm for adaptive rejection sampling.
Proceedings of the Algorithmic Learning Theory, 2019

2018
Optimal Adaptation for Early Stopping in Statistical Inverse Problems.
SIAM/ASA J. Uncertain. Quantification, 2018

Parallelizing Spectrally Regularized Kernel Algorithms.
J. Mach. Learn. Res., 2018

Optimal Rates for Regularization of Statistical Inverse Learning Problems.
Found. Comput. Math., 2018

2017
Compressive Statistical Learning with Random Feature Moments.
CoRR, 2017

2016
Extensions of stability selection using subsamples of observations and covariates.
Stat. Comput., 2016

2015
Permutational Rademacher Complexity - A New Complexity Measure for Transductive Learning.
Proceedings of the Algorithmic Learning Theory - 26th International Conference, 2015

2014
The f-Adjusted Graph Laplacian: a Diagonal Modification with a Geometric Interpretation.
Proceedings of the 31th International Conference on Machine Learning, 2014

Localized Complexities for Transductive Learning.
Proceedings of The 27th Conference on Learning Theory, 2014

Decontamination of Mutually Contaminated Models.
Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014

2013
Classification with Asymmetric Label Noise: Consistency and Maximal Denoising
CoRR, 2013

Classification with Asymmetric Label Noise: Consistency and Maximal Denoising.
Proceedings of the COLT 2013, 2013

2012
On the convergence rate of lp-norm multiple kernel learning.
J. Mach. Learn. Res., 2012

Exemplar-based image inpainting: Fast priority and coherent nearest neighbor search.
Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing, 2012

Early stopping for mutual information based feature selection.
Proceedings of the 21st International Conference on Pattern Recognition, 2012

A Simple Extension of Stability Feature Selection.
Proceedings of the Pattern Recognition, 2012

2011
The Local Rademacher Complexity of Lp-Norm Multiple Kernel Learning.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Generalizing from Several Related Classification Tasks to a New Unlabeled Sample.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

2010
Semi-Supervised Novelty Detection.
J. Mach. Learn. Res., 2010

Kernel Partial Least Squares is Universally Consistent.
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

µTOSS - Multiple hypothesis testing in an open software system.
Proceedings of the First Workshop on Applications of Pattern Analysis, 2010

Optimal learning rates for Kernel Conjugate Gradient regression.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

2009
Novelty detection: Unlabeled data definitely help.
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009

Adaptive False Discovery Rate Control under Independence and Dependence.
J. Mach. Learn. Res., 2009

2008
Approximating the Best Linear Unbiased Estimator of Non-Gaussian Signals with Gaussian Noise.
IEICE Trans. Inf. Syst., 2008

2007
Optimal dyadic decision trees.
Mach. Learn., 2007

Statistical properties of kernel principal component analysis.
Mach. Learn., 2007

Occam's Hammer.
Proceedings of the Learning Theory, 20th Annual Conference on Learning Theory, 2007

Resampling-Based Confidence Regions and Multiple Tests for a Correlated Random Vector.
Proceedings of the Learning Theory, 20th Annual Conference on Learning Theory, 2007

2006
In Search of Non-Gaussian Components of a High-Dimensional Distribution.
J. Mach. Learn. Res., 2006

Occam's hammer: a link between randomized learning and multiple testing FDR control
CoRR, 2006

Obtaining the Best Linear Unbiased Estimator of Noisy Signals by Non-Gaussian Component Analysis.
Proceedings of the 2006 IEEE International Conference on Acoustics Speech and Signal Processing, 2006

A Novel Dimension Reduction Procedure for Searching Non-Gaussian Subspaces.
Proceedings of the Independent Component Analysis and Blind Signal Separation, 2006

2005
On the Convergence of Eigenspaces in Kernel Principal Component Analysis.
Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005

Pattern Recognition from One Example by Chopping.
Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005

Non-Gaussian Component Analysis: a Semi-parametric Framework for Linear Dimension Reduction.
Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005

2004
BCI competition 2003-data set IIa: spatial patterns of self-controlled brain rhythm modulations.
IEEE Trans. Biomed. Eng., 2004

Un algorithme accéléré d'échantillonnage bayésien pour le modèle CART.
Rev. d'Intelligence Artif., 2004

Different Paradigms for Choosing Sequential Reweighting Algorithms.
Neural Comput., 2004

Kernel Projection Machine: a New Tool for Pattern Recognition.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

Oracle Bounds and Exact Algorithm for Dyadic Classification Trees.
Proceedings of the Learning Theory, 17th Annual Conference on Learning Theory, 2004

2003
On the Rate of Convergence of Regularized Boosting Classifiers.
J. Mach. Learn. Res., 2003


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