2 citations · 2 across the 6 of their papers we have counts for
6 papers
Generalization Bounds for Inductive Matrix Completion in Low-noise Settings
Antoine Ledent, Rodrigo Alves, Yunwen Lei +2
We study inductive matrix completion (matrix completion with side information) under an i.i.d. subgaussian noise assumption at a low noise regime, with uniform sampling of the entr…
Rademacher Complexity and Generalization Performance of Multi-category Margin Classifiers
Khadija Musayeva, Fabien Lauer, Yann Guermeur
One of the main open problems in the theory of multi-category margin classification is the form of the optimal dependency of a guaranteed risk on the number C of categories, the sa…
Combinatorial and Structural Results for gamma-Psi-dimensions
Yann Guermeur
This article deals with the generalization performance of margin multi-category classifiers, when minimal learnability hypotheses are made. In that context, the derivation of a gua…
L p -norm Sauer-Shelah Lemma for Margin Multi-category Classifiers
Yann Guermeur
In the framework of agnostic learning, one of the main open problems of the theory of multi-category pattern classification is the characterization of the way the complexity varies…
A Quadratic Loss Multi-Class SVM
Emmanuel Monfrini, Yann Guermeur
Using a support vector machine requires to set two types of hyperparameters: the soft margin parameter C and the parameters of the kernel. To perform this model selection task, the…
Scale-sensitive Psi-dimensions: the Capacity Measures for Classifiers Taking Values in R^Q
Yann Guermeur
Bounds on the risk play a crucial role in statistical learning theory. They usually involve as capacity measure of the model studied the VC dimension or one of its extensions. In c…