6 citations · 9 across the 6 of their papers we have counts for
7 papers
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…
An efficient joint model for high dimensional longitudinal and survival data via generic association features
Van Tuan Nguyen, Adeline Fermanian, Agathe Guilloux +4
This paper introduces a prognostic method called FLASH that addresses the problem of joint modelling of longitudinal data and censored durations when a large number of both longitu…
Online Inventory Problems: Beyond the i.i.d. Setting with Online Convex Optimization
Massil Hihat, Stéphane Gaïffas, Guillaume Garrigos +1
We study multi-product inventory control problems where a manager makes sequential replenishment decisions based on partial historical information in order to minimize its cumulati…
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…
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…
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…
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…