4 citations · 11 across the 15 of their papers we have counts for
5 papers · 1 filter
Love or Hate? Share or Split? Privacy-Preserving Training Using Split Learning and Homomorphic Encryption
Tanveer Khan, Khoa Nguyen, Antonis Michalas +1
Split learning (SL) is a new collaborative learning technique that allows participants, e.g. a client and a server, to train machine learning models without the client sharing raw…
A More Secure Split: Enhancing the Security of Privacy-Preserving Split Learning
Tanveer Khan, Khoa Nguyen, Antonis Michalas
Split learning (SL) is a new collaborative learning technique that allows participants, e.g. a client and a server, to train machine learning models without the client sharing raw…
Learning in the Dark: Privacy-Preserving Machine Learning using Function Approximation
Tanveer Khan, Antonis Michalas
Over the past few years, a tremendous growth of machine learning was brought about by a significant increase in adoption and implementation of cloud-based services. As a result, va…
Split Without a Leak: Reducing Privacy Leakage in Split Learning
Khoa Nguyen, Tanveer Khan, Antonis Michalas
The popularity of Deep Learning (DL) makes the privacy of sensitive data more imperative than ever. As a result, various privacy-preserving techniques have been implemented to pres…
Split Ways: Privacy-Preserving Training of Encrypted Data Using Split Learning
Tanveer Khan, Khoa Nguyen, Antonis Michalas
Split Learning (SL) is a new collaborative learning technique that allows participants, e.g. a client and a server, to train machine learning models without the client sharing raw…