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20162024
most citedBinarsity: a penalization for one-hot encoded features in linear supervised learning

6 citations · 9 across the 6 of their papers we have counts for

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5 papers · 1 filter

stat.ML2024★ 1 cited

Multivariate Online Linear Regression for Hierarchical Forecasting

Massil Hihat, Guillaume Garrigos, Adeline Fermanian +1

In this paper, we consider a deterministic online linear regression model where we allow the responses to be multivariate. To address this problem, we introduce MultiVAW, a method…

stat.ML2018★ 1 cited

Comparison of methods for early-readmission prediction in a high-dimensional heterogeneous covariates and time-to-event outcome framework

Simon Bussy, Raphaël Veil, Vincent Looten +5

Background: Choosing the most performing method in terms of outcome prediction or variables selection is a recurring problem in prognosis studies, leading to many publications on m…

stat.ML2018

Binacox: automatic cut-point detection in high-dimensional Cox model with applications in genetics

Simon Bussy, Mokhtar Z. Alaya, Anne-Sophie Jannot +1

We introduce the binacox, a prognostic method to deal with the problem of detecting multiple cut-points per features in a multivariate setting where a large number of continuous fe…

stat.ML2017★ 6 cited

Binarsity: a penalization for one-hot encoded features in linear supervised learning

Mokhtar Z. Alaya, Simon Bussy, Stéphane Gaïffas +1

This paper deals with the problem of large-scale linear supervised learning in settings where a large number of continuous features are available. We propose to combine the well-kn…

stat.ML2016★ 1 cited

C-mix: a high dimensional mixture model for censored durations, with applications to genetic data

Simon Bussy, Agathe Guilloux, Stéphane Gaïffas +1

We introduce a mixture model for censored durations (C-mix), and develop maximum likelihood inference for the joint estimation of the time distributions and latent regression param…