136 citations · 156 across the 4 of their papers we have counts for
7 papers
Implicit Regularization in Deep Tensor Factorization
Paolo Milanesi, Hachem Kadri, Stéphane Ayache +1
Attempts of studying implicit regularization associated to gradient descent (GD) have identified matrix completion as a suitable test-bed. Late findings suggest that this phenomeno…
Mapping individual differences in cortical architecture using multi-view representation learning
Akrem Sellami, François-Xavier Dupé, Bastien Cagna +4
In neuroscience, understanding inter-individual differences has recently emerged as a major challenge, for which functional magnetic resonance imaging (fMRI) has proven invaluable.…
Deep Networks with Adaptive Nyström Approximation
Luc Giffon, Stéphane Ayache, Thierry Artières +1
Recent work has focused on combining kernel methods and deep learning to exploit the best of the two approaches. Here, we introduce a new architecture of neural networks in which w…
Unsupervised Object Segmentation by Redrawing
Mickaël Chen, Thierry Artières, Ludovic Denoyer
Object segmentation is a crucial problem that is usually solved by using supervised learning approaches over very large datasets composed of both images and corresponding object ma…
A Meta-Learning Approach to One-Step Active Learning
Gabriella Contardo, Ludovic Denoyer, Thierry Artieres
We consider the problem of learning when obtaining the training labels is costly, which is usually tackled in the literature using active-learning techniques. These approaches prov…
Sequential Cost-Sensitive Feature Acquisition
Gabriella Contardo, Ludovic Denoyer, Thierry Artières
We propose a reinforcement learning based approach to tackle the cost-sensitive learning problem where each input feature has a specific cost. The acquisition process is handled th…