output
20202022
most citedFree-rider Attacks on Model Aggregation in Federated Learning

12 citations

10 papers

cs.LG2022★ 4 cited

SIFU: Sequential Informed Federated Unlearning for Efficient and Provable Client Unlearning in Federated Optimization

Yann Fraboni, Martin Van Waerebeke, Kevin Scaman +3

Machine Unlearning (MU) is an increasingly important topic in machine learning safety, aiming at removing the contribution of a given data point from a training procedure. Federate…

math.ST2022★ 1 cited

A geometric framework for asymptotic inference of principal subspaces in PCA

Dimbihery Rabenoro, Xavier Pennec

In this article, we develop an asymptotic method for constructing confidence regions for the set of all linear subspaces arising from PCA, from which we derive hypothesis tests on…

cs.LG2022★ 11 cited

A General Theory for Federated Optimization with Asynchronous and Heterogeneous Clients Updates

Yann Fraboni, Richard Vidal, Laetitia Kameni +1

We propose a novel framework to study asynchronous federated learning optimization with delays in gradient updates. Our theoretical framework extends the standard FedAvg aggregatio…

cs.CV2022

Privacy Preserving Image Registration

Riccardo Taiello, Melek Önen, Francesco Capano +2

Image registration is a key task in medical imaging applications, allowing to represent medical images in a common spatial reference frame. Current approaches to image registration…

math.OC2022★ 3 cited

Low-rank optimization methods based on projected projected-gradient descent that accumulate at Bouligand stationary points

Guillaume Olikier, Kyle A. Gallivan, P. -A. Absil

This paper considers the problem of minimizing a differentiable function with locally Lipschitz continuous gradient on the algebraic variety of real matrices of upper-bounded rank.…

eess.IV2021

Robust joint registration of multiple stains and MRI for multimodal 3D histology reconstruction: Application to the Allen human brain atlas

Adrià Casamitjana, Marco Lorenzi, Sebastiano Ferraris +6

Joint registration of a stack of 2D histological sections to recover 3D structure (``3D histology reconstruction'') finds application in areas such as atlas building and validation…