13 citations · 19 across the 3 of their papers we have counts for
3 papers
Knowledge from Uncertainty in Evidential Deep Learning
Cai Davies, Marc Roig Vilamala, Alun D. Preece +3
This work reveals an evidential signal that emerges from the uncertainty value in Evidential Deep Learning (EDL). EDL is one example of a class of uncertainty-aware deep learning a…
On the amplification of security and privacy risks by post-hoc explanations in machine learning models
Pengrui Quan, Supriyo Chakraborty, Jeya Vikranth Jeyakumar +1
A variety of explanation methods have been proposed in recent years to help users gain insights into the results returned by neural networks, which are otherwise complex and opaque…
SparseFed: Mitigating Model Poisoning Attacks in Federated Learning with Sparsification
Ashwinee Panda, Saeed Mahloujifar, Arjun N. Bhagoji +2
Federated learning is inherently vulnerable to model poisoning attacks because its decentralized nature allows attackers to participate with compromised devices. In model poisoning…