activity
20172022
most citedFixed effects selection in the linear mixed-effects model using adaptive ridge procedure for L0 penalty performance

1 citations · 3 across the 5 of their papers we have counts for

collaborators

5 papers

stat.ML2022★ 1 cited

Functional Anomaly Detection: a Benchmark Study

Guillaume Staerman, Eric Adjakossa, Pavlo Mozharovskyi +3

The increasing automation in many areas of the Industry expressly demands to design efficient machine-learning solutions for the detection of abnormal events. With the ubiquitous d…

math.ST2021

Sign Consistency of the Generalized Elastic Net Estimator

Wencan Zhu, Eric Adjakossa, Céline Lévy-Leduc +1

In this paper, we propose a novel variable selection approach in the framework of high-dimensional linear models where the columns of the design matrix are highly correlated. It co…

cs.LG2020★ 1 cited

Kalman Recursions Aggregated Online

Eric Adjakossa, Yannig Goude, Olivier Wintenberger

In this article, we aim at improving the prediction of expert aggregation by using the underlying properties of the models that provide expert predictions. We restrict ourselves to…

stat.ME2017★ 1 cited

Fixed effects selection in the linear mixed-effects model using adaptive ridge procedure for L0 penalty performance

Eric Adjakossa, Grégory Nuel

This paper is concerned with the selection of fixed effects along with the estimation of fixed effects, random effects and variance components in the linear mixed-effects model. We…

stat.ME2017

Profiled deviance for the multivariate linear mixed-effects model fitting

Eric Adjakossa, Grégory Nuel

This paper focuses on the multivariate linear mixed-effects model, including all the correlations between the random effects when the marginal residual terms are assumed uncorrelat…