Alain Celisse - researchr alias

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Viewing Publication 1 - 11 from 11

2025

Minimum discrepancy principle strategy for choosing k in k-NN regressionYaroslav Averyanov, Alain Celisse. ml, 114(5):118, 2025. [doi]

2023

R Package Implementing Correlated Variable Selection by Hierarchical Clustering and Group-LassoQuentin Grimonprez, Samuel Blanck, Alain Celisse, Guillemette Marot. jstatsoft, 106(3), 2023. [doi]

2021

Analyzing the discrepancy principle for kernelized spectral filter learning algorithmsAlain Celisse, Martin Wahl. jmlr, 22, 2021. [doi]

2019

A Kernel Multiple Change-point Algorithm via Model SelectionSylvain Arlot, Alain Celisse, Zaïd Harchaoui. jmlr, 20, 2019. [doi]

2018

Theoretical Analysis of Cross-Validation for Estimating the Risk of the $k$-Nearest Neighbor ClassifierAlain Celisse, Tristan Mary-Huard. jmlr, 19, 2018. [doi]

New efficient algorithms for multiple change-point detection with reproducing kernelsAlain Celisse, Guillemette Marot, Morgane Pierre-Jean, Guillem Rigaill. csda, 128:200-220, 2018. [doi]

2014

MPAgenomics: an R package for multi-patient analysis of genomic markersQuentin Grimonprez, Alain Celisse, Samuel Blanck, Meyling Cheok, Martin Figeac, Guillemette Marot. bmcbi, 15:394, 2014. [doi]

2011

Segmentation of the mean of heteroscedastic data via cross-validationSylvain Arlot, Alain Celisse. sac, 21(4):613-632, 2011. [doi]

2009

Kerfdr: a semi-parametric kernel-based approach to local false discovery rate estimationMickaÃ«l Guedj, StÃ©phane Robin, Alain Celisse, GrÃ©gory Nuel. bmcbi, 10, 2009. [doi]

2008

Nonparametric density estimation by exact leave-p-out cross-validationAlain Celisse, Stéphane Robin. csda, 52(5):2350-2368, 2008. [doi]

Model selection via cross-validation in density estimation, regression, and change-point detection. (Sélection de modèle par validation-croisée en estimation de la densité, régression et détection de ruptures)Alain Celisse. PhD thesis, University of Paris-Sud, Orsay, France, 2008. [doi]

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