1 citations · 1 across the 7 of their papers we have counts for
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Exponential-Family Membership Inference: From LiRA and RMIA to BaVarIA
Rickard Brännvall
Membership inference attacks (MIAs) are becoming standard tools for auditing the privacy of machine learning models. The leading attacks -- LiRA (Carlini et al., 2022) and RMIA (Za…
Client-Conditional Federated Learning via Local Training Data Statistics
Rickard Brännvall
Federated learning (FL) under data heterogeneity remains challenging: existing methods either ignore client differences (FedAvg), require costly cluster discovery (IFCA), or mainta…
Conditioning on Local Statistics for Scalable Heterogeneous Federated Learning
Rickard Brännvall
Federated learning is a distributed machine learning approach where multiple clients collaboratively train a model without sharing their local data, which contributes to preserving…
Technical Report for the Forgotten-by-Design Project: Targeted Obfuscation for Machine Learning
Rickard Brännvall, Laurynas Adomaitis, Olof Görnerup +1
The right to privacy, enshrined in various human rights declarations, faces new challenges in the age of artificial intelligence (AI). This paper explores the concept of the Right…