285 citations
- Laboratoire Lorrain de Recherche en Informatique et ses ApplicationsFR32 papers
- Centre National de la Recherche ScientifiqueFR16 papers
- Institut de Recherche en Informatique et Systèmes AléatoiresFR6 papers
- Université Paris CitéFR6 papers
- UCLouvainBE5 papers
- École Normale Supérieure de LyonFR4 papers
- Institut für Regionale Innovation und SozialforschungDE4 papers
- RMIT UniversityAU4 papers
- Université de LorraineFR4 papers
- Université Grenoble AlpesFR4 papers
- Université Paris-SudFR4 papers
- Centre de Recherche en Mathématiques de la DécisionFR3 papers
6 papers · 1 filter
Clustered Multi-Task Learning: A Convex Formulation
Laurent Jacob, Francis Bach, Jean-Philippe Vert
In multi-task learning several related tasks are considered simultaneously, with the hope that by an appropriate sharing of information across tasks, each task may benefit from the…
Exploring Large Feature Spaces with Hierarchical Multiple Kernel Learning
Francis Bach
For supervised and unsupervised learning, positive definite kernels allow to use large and potentially infinite dimensional feature spaces with a computational cost that only depen…
On Probability Distributions for Trees: Representations, Inference and Learning
François Denis, Amaury Habrard, Rémi Gilleron +2
We study probability distributions over free algebras of trees. Probability distributions can be seen as particular (formal power) tree series [Berstel et al 82, Esik et al 03], i.…
Resampling methods for parameter-free and robust feature selection with mutual information
Damien François, Fabrice Rossi, Vincent Wertz +1
Combining the mutual information criterion with a forward feature selection strategy offers a good trade-off between optimality of the selected feature subset and computation time.…
Fast Selection of Spectral Variables with B-Spline Compression
Fabrice Rossi, Damien François, Vincent Wertz +2
The large number of spectral variables in most data sets encountered in spectral chemometrics often renders the prediction of a dependent variable uneasy. The number of variables h…
Mutual information for the selection of relevant variables in spectrometric nonlinear modelling
Fabrice Rossi, Amaury Lendasse, Damien François +2
Data from spectrophotometers form vectors of a large number of exploitable variables. Building quantitative models using these variables most often requires using a smaller set of…