Understanding how the brain processes errors is an essential and active field of neuroscience. Real time extraction and analysis of error signals provide an innovative method of assessing how individuals perceive ongoing interactions without recourse to overt behaviour. This area of research is critical in modern Brain–Computer Interface (BCI)...
-
November 2015 (v1)Journal articleUploaded on: February 28, 2023
-
December 2, 2022 (v1)Conference paper
In federated learning, clients such as mobile devices or data silos (e.g. hospitals and banks) collaboratively improve a shared model, while maintaining their data locally. Multiple recent works show that client's private information can still be disclosed to an adversary who just eavesdrops the messages exchanged between the targeted client...
Uploaded on: February 22, 2023 -
November 20, 2024 (v1)Publication
Federated Learning (FL) enables multiple clients, such as mobile phones and IoT devices, to collaboratively train a global machine learning model while keeping their data localized. However, recent studies have revealed that the training phase of FL is vulnerable to reconstruction attacks, such as attribute inference attacks (AIA), where...
Uploaded on: January 13, 2025 -
February 25, 2025 (v1)Conference paper
Federated Learning (FL) enables multiple clients, such as mobile phones and IoT devices, to collaboratively train a global machine learning model while keeping their data localized. However, recent studies have revealed that the training phase of FL is vulnerable to reconstruction attacks, such as attribute inference attacks (AIA), where...
Uploaded on: January 13, 2025