Stéphane Chrétien
Stéphane Chrétien
Dean of ASSP Faculty and Full professor of Statistics and Machine Learning, University of Lyon 2
Verified email at - Homepage
Cited by
Cited by
A component-wise EM algorithm for mixtures
G Celeux, S Chretien, F Forbes, A Mkhadri
Journal of Computational and Graphical Statistics, 2002
Kullback proximal algorithms for maximum-likelihood estimation
S Chretien, AO Hero
IEEE transactions on information theory 46 (5), 1800-1810, 2000
On EM algorithms and their proximal generalizations
ESAIM: Probability and Statistics 12, 308-326, 2008
Dynamical mean field theory algorithm and experiment on quantum computers
I Rungger, N Fitzpatrick, H Chen, CH Alderete, H Apel, A Cowtan, ...
arXiv preprint arXiv:1910.04735, 2019
Degeneracy in the maximum likelihood estimation of univariate Gaussian mixtures with EM
C Biernacki, S Chretien
Statistics & Probability Letters 61 (4), 373-382, 2003
Dendrochemical assessment of mercury releases from a pond and dredged-sediment landfill impacted by a chlor-alkali plant
F Maillard, O Girardclos, M Assad, C Zappelini, JMP Mena, L Yung, ...
Environmental research 148, 122-126, 2016
An Alternating l1 approach to the compressed sensing problem
S Chrétien
Signal Processing Letters, IEEE 17 (2), 181-184, 2010
Sparse recovery with unknown variance: a LASSO-type approach
S Chrétien, S Darses
IEEE Transactions on Information Theory, 2011
Invertibility of random submatrices via tail decoupling and a Matrix Chernoff Inequality
S Chrétien, S Darses
Statistics and Probability Letters 82 (7), 1479-1487, 2011
Introducing and Comparing Recent Clustering Methods for Massive Data Management in the Internet of Things
C Guyeux, S Chretien, G Bou Tayeh, J Demerjian, J Bahi
Journal of sensor and actuator networks 8 (4), 56, 2019
The Guedon-Vershynin Semi-Definite Programming approach to low dimensional embedding for unsupervised clustering
S Chrétien, C Dombry, A Faivre
Frontiers in Applied Mathematics and Statistics 5, 41, 2019
Boolean learning under noise-perturbations in hardware neural networks
L Andreoli, X Porte, S Chretien, M Jacquot, L Larger, D Brunner
arXiv preprint arXiv:2003.12319, 2020
A post-prognostics decision approach to optimize the commitment of fuel cell systems in stationary applications
S Chrétien, N Herr, JM Nicod, C Varnier
2015 IEEE Conference on Prognostics and Health Management (PHM), 1-7, 2015
Acceleration of the EM algorithm via proximal point iterations
S Chretien, AO Hero
IEEE International Symposium on Information Theory, 1998
Multivariate GARCH estimation via a Bregman-proximal trust-region method
S Chrétien, JP Ortega
Computational Statistics & Data Analysis 76, 210-236, 2014
Cyclic projection methods on a class of nonconvex sets: A class of nonconvex sets
S Chretien, P Bondon
Numerical functional analysis and optimization 17 (1-2), 37-56, 1996
A clustering package for nucleotide sequences using Laplacian Eigenmaps and Gaussian Mixture Model
M Bruneau, T Mottet, S Moulin, M Kerbiriou, F Chouly, S Chretien, ...
Computers in biology and medicine 93, 66-74, 2018
High-overtone bulk acoustic resonator as passive ground penetrating RADAR cooperative targets
JM Friedt, A Saintenoy, S Chrétien, T Baron, E Lebrasseur, T Laroche, ...
Journal of Applied Physics 113 (13), 2013
Gene-expression signature functional annotation of breast cancer tumours in function of age
P Jézéquel, Z Sharif, H Lasla, W Gouraud, C Guérin-Charbonnel, ...
BMC Medical Genomics 8, 1-13, 2015
Mixtures of GAMs for habitat suitability analysis with overdispersed presence/absence data
DRJ Pleydell, S Chrétien
Computational Statistics & Data Analysis 54 (5), 1405-1418, 2010
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