3 citations · 3 across the 3 of their papers we have counts for
4 papers · 1 filter
Non-Vacuous Generalization Bounds: Can Rescaling Invariances Help?
Damien Rouchouse, Antoine Gonon, Rémi Gribonval +1
A central challenge in understanding generalization is to obtain non-vacuous guarantees that go beyond worst-case complexity over data or weight space. Among existing approaches, P…
Symmetry-Aware Bayesian Optimization via Max Kernels
Anthony Bardou, Antoine Gonon, Aryan Ahadinia +1
Bayesian Optimization (BO) is a powerful framework for optimizing noisy, expensive-to-evaluate black-box functions. When the objective exhibits invariances under a group action, ex…
A path-norm toolkit for modern networks: consequences, promises and challenges
Antoine Gonon, Nicolas Brisebarre, Elisa Riccietti +1
This work introduces the first toolkit around path-norms that fully encompasses general DAG ReLU networks with biases, skip connections and any operation based on the extraction of…
Compressive Learning for Semi-Parametric Models
Michael P. Sheehan, Antoine Gonon, Mike E. Davies
In the compressive learning theory, instead of solving a statistical learning problem from the input data, a so-called sketch is computed from the data prior to learning. The sketc…