Hierarchical Federated Learning: Approaches, Applications, and Open Challenges
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Access"
DOI: 10.1109/access.2025.3628455
Abstract: Federated learning (FL) is a machine learning (ML) paradigm that enables models to be trained collaboratively across distributed clients without breaking privacy. By allowing data to remain on clients’ devices and only sharing model updates,… read more here.
Keywords: approaches applications; open challenges; applications open; learning approaches ... See more keywords
Knowledge Graph Embedding: A Survey of Approaches and Applications
Sign Up to like & getrecommendations! Published in 2017 at "IEEE Transactions on Knowledge and Data Engineering"
DOI: 10.1109/tkde.2017.2754499
Abstract: Knowledge graph (KG) embedding is to embed components of a KG including entities and relations into continuous vector spaces, so as to simplify the manipulation while preserving the inherent structure of the KG. It can… read more here.
Keywords: graph embedding; embedding survey; knowledge graph; approaches applications ... See more keywords
Approaches and Applications of Mentha Species in Sustainable Agriculture
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DOI: 10.3390/su15065245
Abstract: The potential applications of the genus Mentha as natural pesticides and environmentally friendly postharvest treatments for agricultural products in sustainable agriculture are reviewed here. The non-commercialized Mentha species in Greece and the rest of the… read more here.
Keywords: crop; approaches applications; agriculture; sustainable agriculture ... See more keywords