Gilles Blanchard - Google Scholar Citations

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Co-authors

Clayton ScottProfessor of Electrical Engineering and Computer Science, University of MichiganVerified email at umich.edu
Klaus-Robert MüllerProfessor for Machine Learning, TU Berlin, Germany and Korea University, Seoul, Korea and MPIIVerified email at tu-berlin.de
Masashi SugiyamaDirector, RIKEN Center for Advanced Intelligence Project / Professor, The University of TokyoVerified email at k.u-tokyo.ac.jp
Motoaki KawanabeSenior Researcher, Advanced Telecommunications Research Institute InternationalVerified email at atr.jp
Olivier BousquetGoogleVerified email at m4x.org
Nicole MückeUniversity of StuttgartVerified email at mathematik.uni-stuttgart.de
Vladimir SpokoinyProfessor for Statistics, Humboldt University und WIAS BerlinVerified email at wias-berlin.de
Dr. Nicole KrämerStaburo GmbHVerified email at staburo.de
Marius KloftTU KaiserslauternVerified email at cs.uni-kl.de
Sylvain ArlotUniversité Paris-SaclayVerified email at math.u-psud.fr
rozenholc yvesUniversité Paris DescartesVerified email at parisdescartes.fr
Christin Schäferacs plus GmbHVerified email at acs-plus.de
Pierre NeuvialCNRS, Institut de Mathématiques de ToulouseVerified email at math.univ-toulouse.fr
Thorsten DickhausProfessor of Mathematical Statistics at University of BremenVerified email at uni-bremen.de
Urun DoganResearcher, MicrosoftVerified email at microsoft.com
Rémi GribonvalInria & ENS de LyonVerified email at ens-lyon.fr
François FleuretIdiapVerified email at fleuret.org
Ulrike von LuxburgUniversity of TuebingenVerified email at informatik.uni-tuebingen.de
Donald GemanJohns Hopkins University, Center for Imaging ScienceVerified email at jhu.edu
Nicolas KerivenCNRS, GIPSA-labVerified email at gipsa-lab.grenoble-inp.fr

Gilles Blanchard

Professor of Statistics, University of Paris-Saclay

Verified email at math.u-psud.fr - Homepage

Statistics Machine Learning Pattern Recognition Statistical Learning Theory


Title	Cited by	Year
Semi-supervised novelty detection G Blanchard, G Lee, C Scott Journal of Machine Learning Research 11, 2973-3009, 2010	179	2010
Statistical performance of support vector machines G Blanchard, O Bousquet, P Massart The Annals of Statistics 36 (2), 489-531, 2008	164	2008
BCI competition 2003-data set IIa: spatial patterns of self-controlled brain rhythm modulations G Blanchard, B Blankertz IEEE transactions on biomedical engineering 51 (6), 1062-1066, 2004	150	2004
On the rate of convergence of regularized boosting classifiers G Blanchard, G Lugosi, N Vayatis Journal of Machine Learning Research 4, 861-894, 2003	131	2003
Adaptive false discovery rate control under independence and dependence G Blanchard, É Roquain Journal of Machine Learning Research 10, 2837-2871, 2009	129	2009
On the convergence of eigenspaces in kernel principal component analysis L Zwald, G Blanchard Advances in Neural Information Processing Systems (NIPS 2005) 18, 1649-1656, 2006	120	2006
Statistical properties of kernel principal component analysis G Blanchard, O Bousquet, L Zwald Machine Learning 66 (2-3), 259-294, 2007	119	2007
Classification with asymmetric label noise: Consistency and maximal denoising C Scott, G Blanchard, G Handy Conference on Learning Theory (COLT 2013), 489-511, 2013	110	2013
Hierarchical testing designs for pattern recognition G Blanchard, D Geman The Annals of Statistics 33 (3), 1155-1202, 2005	91	2005
Two simple sufficient conditions for FDR control G Blanchard, E Roquain Electronic journal of statistics 2, 963-992, 2008	83	2008
Generalizing from several related classification tasks to a new unlabeled sample G Blanchard, G Lee, C Scott Advances in neural information processing systems (NIPS 2011), 2178-2186, 2011	82	2011
In search of non-Gaussian components of a high-dimensional distribution G Blanchard, M Kawanabe, M Sugiyama, V Spokoiny, KR Müller Journal of Machine Learning Research 7, 247-282, 2006	81	2006
Optimal learning rates for kernel conjugate gradient regression G Blanchard, N Krämer Advances in Neural Information Processing Systems (NIPS 2010), 226-234, 2010	56	2010
Optimal dyadic decision trees G Blanchard, C Schäfer, Y Rozenholc, KR Müller Machine Learning 66 (2-3), 209-241, 2007	56	2007
Novelty detection: Unlabeled data definitely help C Scott, G Blanchard AISTATS 2009, 464-471, 2009	54	2009
Some nonasymptotic results on resampling in high dimension, I: Confidence regions S Arlot, G Blanchard, E Roquain The Annals of Statistics 38 (1), 51-82, 2010	46	2010
Exemplar-based image inpainting: Fast priority and coherent nearest neighbor search R Martínez-Noriega, A Roumy, G Blanchard 2012 IEEE International workshop on machine learning for signal processing, 1-6, 2012	45	2012
The local Rademacher complexity of lp-norm multiple kernel learning M Kloft, G Blanchard Advances in Neural Information Processing Systems (NIPS 2011), 2438-2446, 2011	45	2011
Kernel projection machine: a new tool for pattern recognition L Zwald, G Blanchard, P Massart, R Vert Advances in Neural Information Processing Systems (NIPS 2004) 17, 1649-1656, 2004	45	2004
Optimal rates for regularization of statistical inverse learning problems G Blanchard, N Mücke Foundations of Computational Mathematics 18 (4), 971-1013, 2018	44	2018

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