Gilles Blanchard

70 papers A* 9A 5B 4Journal 39Unranked 13
YearRankTypeTitle / Venue / Authors
2025 J jnl
Transductive Conformal Inference for Ranking.
CoRR
Jean-Baptiste Fermanian, Pierre Humbert, Gilles Blanchard
2024 J jnl
Estimation of multiple mean vectors in high dimension.
CoRR
Gilles Blanchard, Jean-Baptiste Fermanian, Hannah Marienwald
2024 J jnl
False discovery proportion envelopes with m-consistency.
J. Mach. Learn. Res.
Iqraa Meah, Gilles Blanchard, Étienne Roquain
2024 A conf
Transductive conformal inference with adaptive scores.
AISTATS
Ulysse Gazin, Gilles Blanchard, Étienne Roquain
2023 B conf
Constant regret for sequence prediction with limited advice.
ALT
El Mehdi Saad, Gilles Blanchard
2023 J jnl
Covariance Adaptive Best Arm Identification.
CoRR
El Mehdi Saad, Gilles Blanchard, Nicolas Verzelen
2023 A* conf
Covariance-adaptive best arm identification.
NeurIPS
El Mehdi Saad, Gilles Blanchard, Nicolas Verzelen
2023 — conf
Label Shift Quantification with Robustness Guarantees via Distribution Feature Matching.
ECML/PKDD (5)
Bastien Dussap, Gilles Blanchard, Badr-Eddine Chérief-Abdellatif
2023 J jnl
Label Shift Quantification with Robustness Guarantees via Distribution Feature Matching.
CoRR
Bastien Dussap, Gilles Blanchard, Badr-Eddine Chérief-Abdellatif
2023 J jnl
Transductive conformal inference with adaptive scores.
CoRR
Ulysse Gazin, Gilles Blanchard, Étienne Roquain
2022 J jnl
Topologically penalized regression on manifolds.
J. Mach. Learn. Res.
Olympio Hacquard, Krishnakumar Balasubramanian, Gilles Blanchard, Clément Levrard, Wolfgang Polonik
2021 J jnl
Domain Generalization by Marginal Transfer Learning.
J. Mach. Learn. Res.
Gilles Blanchard, Aniket Anand Deshmukh, Ürün Dogan, Gyemin Lee, Clayton Scott
2021 J jnl
Error rate control for classification rules in multiclass mixture models.
CoRR
Tristan Mary-Huard, Vittorio Perduca, Gilles Blanchard, Marie-Laure Martin-Magniette
2021 A* conf
Fast rates for prediction with limited expert advice.
NeurIPS
El Mehdi Saad, Gilles Blanchard
2021 A conf
High-Dimensional Multi-Task Averaging and Application to Kernel Mean Embedding.
AISTATS
Hannah Marienwald, Jean-Baptiste Fermanian, Gilles Blanchard
2021 J jnl
Nonasymptotic one-and two-sample tests in high dimension with unknown covariance structure.
CoRR
Gilles Blanchard, Jean-Baptiste Fermanian
2021 J jnl
Topologically penalized regression on manifolds.
CoRR
Olympio Hacquard, Krishnakumar Balasubramanian, Gilles Blanchard, Wolfgang Polonik, Clément Levrard
2020 J jnl
High-Dimensional Multi-Task Averaging and Application to Kernel Mean Embedding.
CoRR
Hannah Marienwald, Jean-Baptiste Fermanian, Gilles Blanchard
2020 J jnl
Online Orthogonal Matching Pursuit.
CoRR
El Mehdi Saad, Gilles Blanchard, Sylvain Arlot
2020 J jnl
Statistical Learning Guarantees for Compressive Clustering and Compressive Mixture Modeling.
CoRR
Rémi Gribonval, Gilles Blanchard, Nicolas Keriven, Yann Traonmilin
2019 B conf
A minimax near-optimal algorithm for adaptive rejection sampling.
ALT
Juliette Achdou, Joseph Lam-Weil, Alexandra Carpentier, Gilles Blanchard
2019 J jnl
Decontamination of Mutual Contamination Models.
J. Mach. Learn. Res.
Julian Katz-Samuels, Gilles Blanchard, Clayton Scott
2019 J jnl
Efficient Regularized Piecewise-Linear Regression Trees.
CoRR
Leonidas Lefakis, Oleksandr Zadorozhnyi, Gilles Blanchard
2019 J jnl
Restless dependent bandits with fading memory.
CoRR
Oleksandr Zadorozhnyi, Gilles Blanchard, Alexandra Carpentier
2019 J jnl
Volume Doubling Condition and a Local Poincaré Inequality on Unweighted Random Geometric Graphs.
CoRR
Franziska Göbel, Gilles Blanchard
2018 J jnl
A minimax near-optimal algorithm for adaptive rejection sampling.
CoRR
Juliette Achdou, Joseph C. Lam, Alexandra Carpentier, Gilles Blanchard
2018 J jnl
Optimal Adaptation for Early Stopping in Statistical Inverse Problems.
SIAM/ASA J. Uncertain. Quantification
Gilles Blanchard, Marc Hoffmann, Markus Reiß
2018 J jnl
Optimal Rates for Regularization of Statistical Inverse Learning Problems.
Found. Comput. Math.
Gilles Blanchard, Nicole Mücke
2018 J jnl
Parallelizing Spectrally Regularized Kernel Algorithms.
J. Mach. Learn. Res.
Nicole Mücke, Gilles Blanchard
2017 J jnl
Compressive Statistical Learning with Random Feature Moments.
CoRR
Rémi Gribonval, Gilles Blanchard, Nicolas Keriven, Yann Traonmilin
2016 J jnl
Extensions of stability selection using subsamples of observations and covariates.
Stat. Comput.
Andre Beinrucker, Ürün Dogan, Gilles Blanchard
2015 B conf
Permutational Rademacher Complexity - A New Complexity Measure for Transductive Learning.
ALT
Ilya O. Tolstikhin, Nikita Zhivotovskiy, Gilles Blanchard
2015 J jnl
Permutational Rademacher Complexity: a New Complexity Measure for Transductive Learning.
CoRR
Ilya O. Tolstikhin, Nikita Zhivotovskiy, Gilles Blanchard
2014 A conf
Decontamination of Mutually Contaminated Models.
AISTATS
Gilles Blanchard, Clayton Scott
2014 A* conf
Localized Complexities for Transductive Learning.
COLT
Ilya O. Tolstikhin, Gilles Blanchard, Marius Kloft
2014 J jnl
Localized Complexities for Transductive Learning.
CoRR
Ilya O. Tolstikhin, Gilles Blanchard, Marius Kloft
2014 A* conf
The f-Adjusted Graph Laplacian: a Diagonal Modification with a Geometric Interpretation.
ICML
Sven Kurras, Ulrike von Luxburg, Gilles Blanchard
2013 J jnl
Classification with Asymmetric Label Noise: Consistency and Maximal Denoising
CoRR
Clayton Scott, Gilles Blanchard, Gregory Handy, Sara Pozzi, Marek Flaska
2013 A* conf
Classification with Asymmetric Label Noise: Consistency and Maximal Denoising.
COLT
Clayton Scott, Gilles Blanchard, Gregory Handy
2012 — conf
A Simple Extension of Stability Feature Selection.
DAGM/OAGM Symposium
Andre Beinrucker, Ürün Dogan, Gilles Blanchard
2012 B conf
Early stopping for mutual information based feature selection.
ICPR
Andre Beinrucker, Ürün Dogan, Gilles Blanchard
2012 — conf
Exemplar-based image inpainting: Fast priority and coherent nearest neighbor search.
MLSP
Raúl Martínez-Noriega, Aline Roumy, Gilles Blanchard
2012 J jnl
On the convergence rate of lp-norm multiple kernel learning.
J. Mach. Learn. Res.
Marius Kloft, Gilles Blanchard
2011 — conf
Generalizing from Several Related Classification Tasks to a New Unlabeled Sample.
NIPS
Gilles Blanchard, Gyemin Lee, Clayton Scott
2011 — conf
The Local Rademacher Complexity of Lp-Norm Multiple Kernel Learning.
NIPS
Marius Kloft, Gilles Blanchard
2010 A conf
Kernel Partial Least Squares is Universally Consistent.
AISTATS
Gilles Blanchard, Nicole Krämer
2010 — conf
Optimal learning rates for Kernel Conjugate Gradient regression.
NIPS
Gilles Blanchard, Nicole Krämer
2010 J jnl
Semi-Supervised Novelty Detection.
J. Mach. Learn. Res.
Gilles Blanchard, Gyemin Lee, Clayton Scott
2010 — conf
µTOSS - Multiple hypothesis testing in an open software system.
WAPA
Gilles Blanchard, Thorsten Dickhaus, Niklas Hack, Frank Konietschke, Kornelius Rohmeyer, Jonathan D. Rosenblatt, Marsel Scheer, Wiebke Werft
2009 J jnl
Adaptive False Discovery Rate Control under Independence and Dependence.
J. Mach. Learn. Res.
Gilles Blanchard, Étienne Roquain
2009 A conf
Novelty detection: Unlabeled data definitely help.
AISTATS
Clayton Scott, Gilles Blanchard
2008 J jnl
Approximating the Best Linear Unbiased Estimator of Non-Gaussian Signals with Gaussian Noise.
IEICE Trans. Inf. Syst.
Masashi Sugiyama, Motoaki Kawanabe, Gilles Blanchard, Klaus-Robert Müller
2007 A* conf
Occam's Hammer.
COLT
Gilles Blanchard, François Fleuret
2007 J jnl
Optimal dyadic decision trees.
Mach. Learn.
Gilles Blanchard, Christin Schäfer, Yves Rozenholc, Klaus-Robert Müller
2007 A* conf
Resampling-Based Confidence Regions and Multiple Tests for a Correlated Random Vector.
COLT
Sylvain Arlot, Gilles Blanchard, Étienne Roquain
2007 J jnl
Statistical properties of kernel principal component analysis.
Mach. Learn.
Gilles Blanchard, Olivier Bousquet, Laurent Zwald
2006 — conf
A Novel Dimension Reduction Procedure for Searching Non-Gaussian Subspaces.
ICA
Motoaki Kawanabe, Gilles Blanchard, Masashi Sugiyama, Vladimir G. Spokoiny, Klaus-Robert Müller
2006 J jnl
In Search of Non-Gaussian Components of a High-Dimensional Distribution.
J. Mach. Learn. Res.
Gilles Blanchard, Motoaki Kawanabe, Masashi Sugiyama, Vladimir G. Spokoiny, Klaus-Robert Müller
2006 — conf
Obtaining the Best Linear Unbiased Estimator of Noisy Signals by Non-Gaussian Component Analysis.
ICASSP (3)
Masashi Sugiyama, Motoaki Kawanabe, Gilles Blanchard, Vladimir G. Spokoiny, Klaus-Robert Müller
2006 J jnl
Occam's hammer: a link between randomized learning and multiple testing FDR control
CoRR
Gilles Blanchard, François Fleuret
2005 — conf
Non-Gaussian Component Analysis: a Semi-parametric Framework for Linear Dimension Reduction.
NIPS
Gilles Blanchard, Masashi Sugiyama, Motoaki Kawanabe, Vladimir G. Spokoiny, Klaus-Robert Müller
2005 — conf
On the Convergence of Eigenspaces in Kernel Principal Component Analysis.
NIPS
Laurent Zwald, Gilles Blanchard
2005 — conf
Pattern Recognition from One Example by Chopping.
NIPS
François Fleuret, Gilles Blanchard
2004 J jnl
BCI competition 2003-data set IIa: spatial patterns of self-controlled brain rhythm modulations.
IEEE Trans. Biomed. Eng.
Gilles Blanchard, Benjamin Blankertz
2004 J jnl
Different Paradigms for Choosing Sequential Reweighting Algorithms.
Neural Comput.
Gilles Blanchard
2004 — conf
Kernel Projection Machine: a New Tool for Pattern Recognition.
NIPS
Laurent Zwald, Régis Vert, Gilles Blanchard, Pascal Massart
2004 A* conf
Oracle Bounds and Exact Algorithm for Dyadic Classification Trees.
COLT
Gilles Blanchard, Christin Schäfer, Yves Rozenholc
2004 A* conf
Statistical Properties of Kernel Principal Component Analysis.
COLT
Laurent Zwald, Olivier Bousquet, Gilles Blanchard
2004 J jnl
Un algorithme accéléré d'échantillonnage bayésien pour le modèle CART.
Rev. d'Intelligence Artif.
Gilles Blanchard
2003 J jnl
On the Rate of Convergence of Regularized Boosting Classifiers.
J. Mach. Learn. Res.
Gilles Blanchard, Gábor Lugosi, Nicolas Vayatis