Abstract: Federated learning enables participants to collaboratively train a global model through distributed training without sharing raw data. However, this distributed training is vulnerable to ...

Abstract: Recent years have witnessed a huge demand for artificial intelligence and machine learning applications in wireless edge networks to assist individuals with real-time services. Federated ...

The energy sector is becoming a highly connected cyber-physical ecosystem in which distributed energy resources, electric ...

A privacy-preserving marketing framework applies homomorphic encryption to perform machine learning on encrypted ...

Atharv Kolhar, a staff test automation engineer at Figure AI, says the robotics industry needs a testing philosophy that ...

As patients are divided into ever more narrowly defined subgroups, the number of individuals available for research shrinks dramatically. While this approach improves personalization, it also creates ...