Sergey Dubrovskiy

Decentralized Federated Learning under Resource Constraints: An Empirical Comparison

Decentralized federated learning paradigms are increasingly adopted to support scalable and privacy-preserving training across distributed edge systems. However, existing approaches exhibit significant performance variability under realistic system conditions, including statistical heterogeneity, resource constraints,...

LLM-Assisted Edge Intelligence Framework for Smart Home Energy Management