1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.LG2024
Beyond Slow Signs in High-fidelity Model Extraction
Hanna Foerster, Robert Mullins, Ilia Shumailov +1
Deep neural networks, costly to train and rich in intellectual property value, are increasingly threatened by model extraction attacks that compromise their confidentiality. Previo…
cs.LG2024★ 1 cited
Are we making progress in unlearning? Findings from the first NeurIPS unlearning competition
Eleni Triantafillou, Peter Kairouz, Fabian Pedregosa +12
We present the findings of the first NeurIPS competition on unlearning, which sought to stimulate the development of novel algorithms and initiate discussions on formal and robust…