IEEE

Byzantine-Robust Aggregation for Securing Decentralized Federated Learning

Abstract: Federated Learning (FL) emerges as a distributed machine learning approach that addresses privacy concerns by training AI models locally on devices. Decentralized Federated Learning (DFL) ...
IEEE

SMART-FL: Single-Shot Merged Adaptive Resource-Aware Tensor-Fusion for Efficient Federated Learning in Heterogeneous Cross-Silo Environments

Abstract: Federated Learning (FL) is an evolutionary approach for privacy-preserving distributed machine learning and is particularly significant in cross-silo settings where direct data sharing is ...
Scientific Research Publishing

Research on the Innovative Path of AIGC Enabling University Basic Course Teaching ()

The development of artificial intelligence-generated content (AIGC) technology brings new opportunities for the teaching reform of basic courses in colleges and universities. Based on the technology ...
blockchain

ACM Prize in Computing 2025: Matei Zaharia’s Distributed Systems Breakthroughs Power Large Scale Machine Learning and AI

According to Berkeley AI Research (@berkeley_ai), Matei Zaharia received the 2025 ACM Prize in Computing for visionary work in distributed data systems and computing infrastructure that enable large ...