3 accepted papers
Data privacy is of great concern in cloud machine-learning service platforms when sensitive data are exposed to service providers. While private computing environments (e.g. secure enclaves) and cryptographic approaches (e.g. homomorphic encryption) provide strong privacy protection their computing…
Secure aggregation is a critical component in federated learning (FL), which enables the server to learn the aggregate model of the users without observing their local models. Conventionally, secure aggregation algorithms focus only on ensuring the privacy of individual users in a single training ro…
Due to the surge of cloud-assisted AI services, the problem of designing resilient prediction serving systems that can effectively cope with stragglers and minimize response delays has attracted much interest. The common approach for tackling this problem is replication which assigns the same predic…