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 2025Show all

2 papers · 1 filter

stat.ML2025

Adaptive collaboration for online personalized distributed learning with heterogeneous clients

Constantin Philippenko, Batiste Le Bars, Kevin Scaman +1

We study the problem of online personalized decentralized learning with statistically heterogeneous clients collaborating to accelerate local training. An important challenge i…

stat.ML2025

When to Forget? Complexity Trade-offs in Machine Unlearning

Martin Van Waerebeke, Marco Lorenzi, Giovanni Neglia +1

Machine Unlearning (MU) aims at removing the influence of specific data points from a trained model, striving to achieve this at a fraction of the cost of full model retraining. In…