1 citations · 1 across the 4 of their papers we have counts for
5 papers
Transformative or Conservative? Conservation laws for ResNets and Transformers
Sibylle Marcotte, Rémi Gribonval, Gabriel Peyré
While conservation laws in gradient flow training dynamics are well understood for (mostly shallow) ReLU and linear networks, their study remains largely unexplored for more practi…
Keep the Momentum: Conservation Laws beyond Euclidean Gradient Flows
Sibylle Marcotte, Rémi Gribonval, Gabriel Peyré
Conservation laws are well-established in the context of Euclidean gradient flow dynamics, notably for linear or ReLU neural network training. Yet, their existence and principles f…
Sketch and shift: a robust decoder for compressive clustering
Ayoub Belhadji, Rémi Gribonval
Compressive learning is an emerging approach to drastically reduce the memory footprint of large-scale learning, by first summarizing a large dataset into a low-dimensional sketch…
Revisiting RIP guarantees for sketching operators on mixture models
Ayoub Belhadji, Rémi Gribonval
In the context of sketching for compressive mixture modeling, we revisit existing proofs of the Restricted Isometry Property of sketching operators with respect to certain mixtures…
About the Cost of Central Privacy in Density Estimation
Clément Lalanne, Aurélien Garivier, Rémi Gribonval
We study non-parametric density estimation for densities in Lipschitz and Sobolev spaces, and under central privacy. In particular, we investigate regimes where the privacy budget…