Federated Learning in Edge Computing: Advancements, Security Challenges, and Optimization Strategies
Abstract: Federated Learning (FL) has emerged as a transformative paradigm in edge computing, enabling decentralized model training across distributed devices while preserving data privacy. Unlike ...
A new digital system allows operations on a chip to run in parallel, so an AI program can arrive at the best possible answer ...
Abstract: Semantic communications prioritize transmitting meaningful information over raw data in communication systems. However, these systems face significant optimization challenges, particularly ...
The ISC High Performance conference announced that Professor Dr. Martin Schulz, a leading European expert in large-scale - ...
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