Heterogeneous Federated Learning via Generative Model-Aided Knowledge Distillation in the Edge
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2024.3488565
Abstract: Federated learning (FL) has been popular recently as a framework for training machine learning (ML) models in a distributed and privacy-preserving manner. Traditional FL frameworks often struggle with model and statistical heterogeneity among participating clients,… read more here.
Keywords: learning via; knowledge; distillation; federated learning ... See more keywords
Behavioral Repertoire via Generative Adversarial Policy Networks
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Cognitive and Developmental Systems"
DOI: 10.1109/tcds.2020.3008574
Abstract: Learning algorithms are enabling robots to solve increasingly challenging real-world tasks. These approaches often rely on demonstrations and reproduce the behavior shown. Unexpected changes in the environment or in robot morphology may require using different… read more here.
Keywords: behavioral repertoire; via generative; repertoire via; generative adversarial ... See more keywords