From the 1 of 2.6k papers with an AI index.
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- Centre National de la Recherche ScientifiqueFR646 papers
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- Sorbonne UniversitéFR174 papers
- Université Grenoble AlpesFR119 papers
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- Université Paris-SaclayFR96 papers
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- École Normale Supérieure de LyonFR88 papers
6 papers · 2 filters
Convex Sparse Matrix Factorizations
Francis Bach, Julien Mairal, Jean Ponce
We present a convex formulation of dictionary learning for sparse signal decomposition. Convexity is obtained by replacing the usual explicit upper bound on the dictionary size by…
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.…
Bolasso: model consistent Lasso estimation through the bootstrap
Francis Bach
We consider the least-square linear regression problem with regularization by the l1-norm, a problem usually referred to as the Lasso. In this paper, we present a detailed asymptot…
A New Approach to Collaborative Filtering: Operator Estimation with Spectral Regularization
Jacob Abernethy, Francis Bach, Theodoros Evgeniou +1
We present a general approach for collaborative filtering (CF) using spectral regularization to learn linear operators from "users" to the "objects" they rate. Recent low-rank type…