Kevin Scaman

activity

20222026

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

4 citations · 6 across the 7 of their papers we have counts for

collaborators

Showing 2026Show all

2 papers · 1 filter

cs.LG2026

Variance-Reduced $(ε, δ) -$ Unlearning using Forget Set Gradients

Martin Van Waerebeke, Marco Lorenzi, Kevin Scaman +2

In machine unlearning, $(ε, δ) -$ unlearning is a popular framework that provides formal guarantees on the effectiveness of the removal of a subset of training data, the for…

cs.LG2026

Unbiased Approximate Vector-Jacobian Products for Efficient Backpropagation

Killian Bakong, Laurent Massoulié, Edouard Oyallon +1

In this work we introduce methods to reduce the computational and memory costs of training deep neural networks. Our approach consists in replacing exact vector-jacobian products b…

Variance-Reduced (ε,δ)−Unlearning using Forget Set Gradients

Unbiased Approximate Vector-Jacobian Products for Efficient Backpropagation

Variance-Reduced $(ε, δ) -$ Unlearning using Forget Set Gradients