4 papers
Exact Unlearning from Proxies Induces Closeness Guarantees on Approximate Unlearning
Virgile Dine, Teddy Furon
This paper proposes a paradigm shift linking machine unlearning directly to the structure of the data distributions rather than a mere update of the neural network parameters. We s…
SoK: On the Survivability of Backdoor Attacks on Unconstrained Face Recognition Systems
Quentin Le Roux, Yannick Teglia, Teddy Furon +2
The widespread deployment of Deep Learning-based Face Recognition Systems raises many security concerns. While prior research has identified backdoor vulnerabilities on isolated co…
Improving Unlearning with Model Updates Probably Aligned with Gradients
Virgile Dine, Teddy Furon, Charly Faure
We formulate the machine unlearning problem as a general constrained optimization problem. It unifies the first-order methods from the approximate machine unlearning literature. Th…
Backdoor Attacks on Deep Learning Face Detection
Quentin Le Roux, Yannick Teglia, Teddy Furon +1
Face Recognition Systems that operate in unconstrained environments capture images under varying conditions,such as inconsistent lighting, or diverse face poses. These challenges r…