Abstract: Hierarchical federated learning (HFL) is a privacy-preserving distributed machine learning framework with a client-edge-cloud hierarchy, where multiple edge servers perform partial model ...

Abstract: In disaster scenarios, secure and reliable data collection in Vehicular Ad Hoc Network (VANET) is crucial, yet the network often suffers from issues such as infrastructure damage, network ...

Machine learning techniques that make use of tensor networks could manipulate data more efficiently and help open the black ...

Large language model (LLM) applications often reuse previously processed context, such as chat history and documents, which in troduces significant redundant computation. Existing LLM serving systems ...