15 citations · 15 across the 2 of their papers we have counts for
4 papers
Natural Langevin Dynamics for Neural Networks
Gaétan Marceau-Caron, Yann Ollivier
One way to avoid overfitting in machine learning is to use model parameters distributed according to a Bayesian posterior given the data, rather than the maximum likelihood estimat…
Practical Riemannian Neural Networks
Gaétan Marceau-Caron, Yann Ollivier
We provide the first experimental results on non-synthetic datasets for the quasi-diagonal Riemannian gradient descents for neural networks introduced in [Ollivier, 2015]. These in…
Racing Multi-Objective Selection Probabilities
Gaétan Marceau, Marc Schoenauer
In the context of Noisy Multi-Objective Optimization, dealing with uncertainties requires the decision maker to define some preferences about how to handle them, through some stati…
Computational Methods for Probabilistic Inference of Sector Congestion in Air Traffic Management
Gaétan Marceau, Pierre Savéant, Marc Schoenauer
This article addresses the issue of computing the expected cost functions from a probabilistic model of the air traffic flow and capacity management. The Clenshaw-Curtis quadrature…