3 citations · 3 across the 2 of their papers we have counts for
3 papers
cs.LG2022★ 3 cited
Rethinking Machine Learning Robustness via its Link with the Out-of-Distribution Problem
Abderrahmen Amich, Birhanu Eshete
Despite multiple efforts made towards robust machine learning (ML) models, their vulnerability to adversarial examples remains a challenging problem that calls for rethinking the d…
cs.CR2021
EG-Booster: Explanation-Guided Booster of ML Evasion Attacks
Abderrahmen Amich, Birhanu Eshete
The widespread usage of machine learning (ML) in a myriad of domains has raised questions about its trustworthiness in security-critical environments. Part of the quest for trustwo…
cs.CR2021
Explanation-Guided Diagnosis of Machine Learning Evasion Attacks
Abderrahmen Amich, Birhanu Eshete
Machine Learning (ML) models are susceptible to evasion attacks. Evasion accuracy is typically assessed using aggregate evasion rate, and it is an open question whether aggregate e…