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Gilles Blanchard
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2020 – today
- 2024
- [c31]Ulysse Gazin, Gilles Blanchard, Étienne Roquain:
Transductive conformal inference with adaptive scores. AISTATS 2024: 1504-1512 - [i19]Gilles Blanchard, Jean-Baptiste Fermanian, Hannah Marienwald:
Estimation of multiple mean vectors in high dimension. CoRR abs/2403.15038 (2024) - 2023
- [c30]El Mehdi Saad, Gilles Blanchard:
Constant regret for sequence prediction with limited advice. ALT 2023: 1343-1386 - [c29]El Mehdi Saad, Gilles Blanchard, Nicolas Verzelen:
Covariance-adaptive best arm identification. NeurIPS 2023 - [c28]Bastien Dussap
, Gilles Blanchard, Badr-Eddine Chérief-Abdellatif:
Label Shift Quantification with Robustness Guarantees via Distribution Feature Matching. ECML/PKDD (5) 2023: 69-85 - [i18]El Mehdi Saad, Gilles Blanchard, Nicolas Verzelen:
Covariance Adaptive Best Arm Identification. CoRR abs/2306.02630 (2023) - [i17]Bastien Dussap, Gilles Blanchard, Badr-Eddine Chérief-Abdellatif:
Label Shift Quantification with Robustness Guarantees via Distribution Feature Matching. CoRR abs/2306.04376 (2023) - [i16]Ulysse Gazin, Gilles Blanchard, Étienne Roquain:
Transductive conformal inference with adaptive scores. CoRR abs/2310.18108 (2023) - 2022
- [j18]Olympio Hacquard, Krishnakumar Balasubramanian, Gilles Blanchard, Clément Levrard, Wolfgang Polonik:
Topologically penalized regression on manifolds. J. Mach. Learn. Res. 23: 161:1-161:39 (2022) - 2021
- [j17]Gilles Blanchard, Aniket Anand Deshmukh, Ürün Dogan, Gyemin Lee, Clayton Scott:
Domain Generalization by Marginal Transfer Learning. J. Mach. Learn. Res. 22: 2:1-2:55 (2021) - [c27]Hannah Marienwald, Jean-Baptiste Fermanian, Gilles Blanchard:
High-Dimensional Multi-Task Averaging and Application to Kernel Mean Embedding. AISTATS 2021: 1963-1971 - [c26]El Mehdi Saad, Gilles Blanchard:
Fast rates for prediction with limited expert advice. NeurIPS 2021: 23582-23591 - [i15]Gilles Blanchard, Jean-Baptiste Fermanian:
Nonasymptotic one-and two-sample tests in high dimension with unknown covariance structure. CoRR abs/2109.01730 (2021) - [i14]Tristan Mary-Huard, Vittorio Perduca, Gilles Blanchard, Marie-Laure Martin-Magniette:
Error rate control for classification rules in multiclass mixture models. CoRR abs/2109.14235 (2021) - [i13]Olympio Hacquard, Krishnakumar Balasubramanian, Gilles Blanchard, Wolfgang Polonik, Clément Levrard:
Topologically penalized regression on manifolds. CoRR abs/2110.13749 (2021) - 2020
- [i12]Rémi Gribonval, Gilles Blanchard, Nicolas Keriven
Statistical Learning Guarantees for Compressive Clustering and Compressive Mixture Modeling. CoRR abs/2004.08085 (2020) - [i11]Hannah Marienwald, Jean-Baptiste Fermanian, Gilles Blanchard:
High-Dimensional Multi-Task Averaging and Application to Kernel Mean Embedding. CoRR abs/2011.06794 (2020) - [i10]El Mehdi Saad, Gilles Blanchard, Sylvain Arlot:
Online Orthogonal Matching Pursuit. CoRR abs/2011.11117 (2020)
2010 – 2019
- 2019
- [j16]Julian Katz-Samuels, Gilles Blanchard, Clayton Scott:
Decontamination of Mutual Contamination Models. J. Mach. Learn. Res. 20: 41:1-41:57 (2019) - [c25]Juliette Achdou, Joseph Lam-Weil, Alexandra Carpentier, Gilles Blanchard:
A minimax near-optimal algorithm for adaptive rejection sampling. ALT 2019: 94-126 - [i9]Oleksandr Zadorozhnyi, Gilles Blanchard, Alexandra Carpentier:
Restless dependent bandits with fading memory. CoRR abs/1906.10454 (2019) - [i8]Leonidas Lefakis, Oleksandr Zadorozhnyi, Gilles Blanchard:
Efficient Regularized Piecewise-Linear Regression Trees. CoRR abs/1907.00275 (2019) - [i7]Franziska Göbel, Gilles Blanchard:
Volume Doubling Condition and a Local Poincaré Inequality on Unweighted Random Geometric Graphs. CoRR abs/1907.03192 (2019) - 2018
- [j15]Gilles Blanchard, Nicole Mücke:
Optimal Rates for Regularization of Statistical Inverse Learning Problems. Found. Comput. Math. 18(4): 971-1013 (2018) - [j14]Nicole Mücke, Gilles Blanchard:
Parallelizing Spectrally Regularized Kernel Algorithms. J. Mach. Learn. Res. 19: 30:1-30:29 (2018) - [j13]Gilles Blanchard, Marc Hoffmann, Markus Reiß:
Optimal Adaptation for Early Stopping in Statistical Inverse Problems. SIAM/ASA J. Uncertain. Quantification 6(3): 1043-1075 (2018) - [i6]Juliette Achdou, Joseph C. Lam, Alexandra Carpentier, Gilles Blanchard:
A minimax near-optimal algorithm for adaptive rejection sampling. CoRR abs/1810.09390 (2018) - 2017
- [i5]Rémi Gribonval, Gilles Blanchard, Nicolas Keriven
Compressive Statistical Learning with Random Feature Moments. CoRR abs/1706.07180 (2017) - 2016
- [j12]Andre Beinrucker, Ürün Dogan, Gilles Blanchard:
Extensions of stability selection using subsamples of observations and covariates. Stat. Comput. 26(5): 1059-1077 (2016) - 2015
- [c24]Ilya O. Tolstikhin, Nikita Zhivotovskiy, Gilles Blanchard:
Permutational Rademacher Complexity - A New Complexity Measure for Transductive Learning. ALT 2015: 209-223 - [i4]Ilya O. Tolstikhin, Nikita Zhivotovskiy, Gilles Blanchard:
Permutational Rademacher Complexity: a New Complexity Measure for Transductive Learning. CoRR abs/1505.02910 (2015) - 2014
- [c23]Gilles Blanchard, Clayton Scott:
Decontamination of Mutually Contaminated Models. AISTATS 2014: 1-9 - [c22]Ilya O. Tolstikhin, Gilles Blanchard, Marius Kloft:
Localized Complexities for Transductive Learning. COLT 2014: 857-884 - [c21]Sven Kurras, Ulrike von Luxburg, Gilles Blanchard:
The f-Adjusted Graph Laplacian: a Diagonal Modification with a Geometric Interpretation. ICML 2014: 1530-1538 - [i3]Ilya O. Tolstikhin, Gilles Blanchard, Marius Kloft:
Localized Complexities for Transductive Learning. CoRR abs/1411.7200 (2014) - 2013
- [c20]Clayton Scott, Gilles Blanchard, Gregory Handy:
Classification with Asymmetric Label Noise: Consistency and Maximal Denoising. COLT 2013: 489-511 - [i2]Clayton Scott, Gilles Blanchard, Gregory Handy, Sara Pozzi, Marek Flaska:
Classification with Asymmetric Label Noise: Consistency and Maximal Denoising. CoRR abs/1303.1208 (2013) - 2012
- [j11]Marius Kloft, Gilles Blanchard:
On the convergence rate of lp-norm multiple kernel learning. J. Mach. Learn. Res. 13: 2465-2502 (2012) - [c19]Andre Beinrucker, Ürün Dogan, Gilles Blanchard:
A Simple Extension of Stability Feature Selection. DAGM/OAGM Symposium 2012: 256-265 - [c18]Andre Beinrucker, Ürün Dogan, Gilles Blanchard:
Early stopping for mutual information based feature selection. ICPR 2012: 975-978 - [c17]Raúl Martínez-Noriega, Aline Roumy, Gilles Blanchard:
Exemplar-based image inpainting: Fast priority and coherent nearest neighbor search. MLSP 2012: 1-6 - 2011
- [c16]Gilles Blanchard, Gyemin Lee, Clayton Scott:
Generalizing from Several Related Classification Tasks to a New Unlabeled Sample. NIPS 2011: 2178-2186 - [c15]Marius Kloft, Gilles Blanchard:
The Local Rademacher Complexity of Lp-Norm Multiple Kernel Learning. NIPS 2011: 2438-2446 - 2010
- [j10]Gilles Blanchard, Gyemin Lee, Clayton Scott:
Semi-Supervised Novelty Detection. J. Mach. Learn. Res. 11: 2973-3009 (2010) - [c14]Gilles Blanchard, Nicole Krämer:
Optimal learning rates for Kernel Conjugate Gradient regression. NIPS 2010: 226-234 - [c13]Gilles Blanchard, Thorsten Dickhaus
µTOSS - Multiple hypothesis testing in an open software system. WAPA 2010: 12-19 - [c12]Gilles Blanchard, Nicole Krämer:
Kernel Partial Least Squares is Universally Consistent. AISTATS 2010: 57-64
2000 – 2009
- 2009
- [j9]Gilles Blanchard, Étienne Roquain:
Adaptive False Discovery Rate Control under Independence and Dependence. J. Mach. Learn. Res. 10: 2837-2871 (2009) - [c11]Clayton Scott, Gilles Blanchard:
Novelty detection: Unlabeled data definitely help. AISTATS 2009: 464-471 - 2008
- [j8]Masashi Sugiyama, Motoaki Kawanabe, Gilles Blanchard, Klaus-Robert Müller
Approximating the Best Linear Unbiased Estimator of Non-Gaussian Signals with Gaussian Noise. IEICE Trans. Inf. Syst. 91-D(5): 1577-1580 (2008) - 2007
- [j7]Gilles Blanchard, Christin Schäfer, Yves Rozenholc
Optimal dyadic decision trees. Mach. Learn. 66(2-3): 209-241 (2007) - [j6]Gilles Blanchard, Olivier Bousquet, Laurent Zwald:
Statistical properties of kernel principal component analysis. Mach. Learn. 66(2-3): 259-294 (2007) - [c10]Gilles Blanchard, François Fleuret:
Occam's Hammer. COLT 2007: 112-126 - [c9]Sylvain Arlot, Gilles Blanchard, Étienne Roquain:
Resampling-Based Confidence Regions and Multiple Tests for a Correlated Random Vector. COLT 2007: 127-141 - 2006
- [j5]Gilles Blanchard, Motoaki Kawanabe, Masashi Sugiyama, Vladimir G. Spokoiny, Klaus-Robert Müller:
In Search of Non-Gaussian Components of a High-Dimensional Distribution. J. Mach. Learn. Res. 7: 247-282 (2006) - [c8]Motoaki Kawanabe, Gilles Blanchard, Masashi Sugiyama, Vladimir G. Spokoiny, Klaus-Robert Müller
A Novel Dimension Reduction Procedure for Searching Non-Gaussian Subspaces. ICA 2006: 149-156 - [c7]Masashi Sugiyama, Motoaki Kawanabe, Gilles Blanchard, Vladimir G. Spokoiny, Klaus-Robert Müller
Obtaining the Best Linear Unbiased Estimator of Noisy Signals by Non-Gaussian Component Analysis. ICASSP (3) 2006: 608-611 - [i1]Gilles Blanchard, François Fleuret:
Occam's hammer: a link between randomized learning and multiple testing FDR control. CoRR abs/math/0608713 (2006) - 2005
- [c6]Gilles Blanchard, Masashi Sugiyama, Motoaki Kawanabe, Vladimir G. Spokoiny, Klaus-Robert Müller:
Non-Gaussian Component Analysis: a Semi-parametric Framework for Linear Dimension Reduction. NIPS 2005: 131-138 - [c5]François Fleuret, Gilles Blanchard:
Pattern Recognition from One Example by Chopping. NIPS 2005: 371-378 - [c4]Laurent Zwald, Gilles Blanchard:
On the Convergence of Eigenspaces in Kernel Principal Component Analysis. NIPS 2005: 1649-1656 - 2004
- [j4]Gilles Blanchard:
Different Paradigms for Choosing Sequential Reweighting Algorithms. Neural Comput. 16(4): 811-836 (2004) - [j3]Gilles Blanchard:
Un algorithme accéléré d'échantillonnage bayésien pour le modèle CART. Rev. d'Intelligence Artif. 18(3): 383-410 (2004) - [j2]Gilles Blanchard, Benjamin Blankertz:
BCI competition 2003-data set IIa: spatial patterns of self-controlled brain rhythm modulations. IEEE Trans. Biomed. Eng. 51(6): 1062-1066 (2004) - [c3]Gilles Blanchard, Christin Schäfer, Yves Rozenholc
Oracle Bounds and Exact Algorithm for Dyadic Classification Trees. COLT 2004: 378-392 - [c2]Laurent Zwald, Olivier Bousquet, Gilles Blanchard:
Statistical Properties of Kernel Principal Component Analysis. COLT 2004: 594-608 - [c1]Laurent Zwald, Régis Vert, Gilles Blanchard, Pascal Massart:
Kernel Projection Machine: a New Tool for Pattern Recognition. NIPS 2004: 1649-1656 - 2003
- [j1]Gilles Blanchard, Gábor Lugosi, Nicolas Vayatis:
On the Rate of Convergence of Regularized Boosting Classifiers. J. Mach. Learn. Res. 4: 861-894 (2003)
Coauthor Index
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