no code implementations • 24 Oct 2023 • Xinglong Chang, Katharina Dost, Gillian Dobbie, Jörg Wicker
This paper presents a novel fully-agnostic framework, DIVA (Detecting InVisible Attacks), that detects attacks solely relying on analyzing the potentially poisoned data set.
no code implementations • 16 Oct 2023 • Xinglong Chang, Gillian Dobbie, Jörg Wicker
To demonstrate this risk is inherited in the adversary's objective, we propose FALFA (Fast Adversarial Label-Flipping Attack), a novel efficient attack for crafting adversarial labels.
1 code implementation • 17 Apr 2023 • Zac Pullar-Strecker, Xinglong Chang, Liam Brydon, Ioannis Ziogas, Katharina Dost, Jörg Wicker
Running complex sets of machine learning experiments is challenging and time-consuming due to the lack of a unified framework.
1 code implementation • 2 May 2021 • Xinglong Chang, Katharina Dost, Kaiqi Zhao, Ambra Demontis, Fabio Roli, Gill Dobbie, Jörg Wicker
Applicability Domain defines a domain based on the known compounds and rejects any unknown compound that falls outside the domain.