3 papers
cs.LG2023
Gradient scarcity with Bilevel Optimization for Graph Learning
Hashem Ghanem, Samuel Vaiter, Nicolas Keriven
A common issue in graph learning under the semi-supervised setting is referred to as gradient scarcity. That is, learning graphs by minimizing a loss on a subset of nodes causes ed…
math.OC2021
Supervised learning of analysis-sparsity priors with automatic differentiation
Hashem Ghanem, Joseph Salmon, Nicolas Keriven +1
Sparsity priors are commonly used in denoising and image reconstruction. For analysis-type priors, a dictionary defines a representation of signals that is likely to be sparse. In…
cs.LG2020
Fast Graph Kernel with Optical Random Features
Hashem Ghanem, Nicolas Keriven, Nicolas Tremblay
The graphlet kernel is a classical method in graph classification. It however suffers from a high computation cost due to the isomorphism test it includes. As a generic proxy, and…