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Leo Brunswic

2 accepted papers

2025

NoT: Federated Unlearning via Weight Negation

CVPR 2025poster

Federated unlearning (FU) aims to remove a participant's data contributions from a trained federated learning (FL) model, ensuring privacy and regulatory compliance. Traditional FU methods often depend on auxiliary storage on either the client or server side or require direct access to the data targ…

Cited by 1SourcePDFScholar
2024

A Theory of Non-acyclic Generative Flow Networks

AAAI 2024technical

GFlowNets is a novel flow-based method for learning a stochastic policy to generate objects via a sequence of actions and with probability proportional to a given positive reward. We contribute to relaxing hypotheses limiting the application range of GFlowNets, in particular: acyclicity (or lack the…

Cited by 4SourcePDFScholar