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Found 4 papers, 0 papers with code
Context-Aware Orchestration of Energy-Efficient Gossip Learning Schemes
To address this issue, we present Optimized Gossip Learning (OGL)}, a distributed training approach based on the combination of GL with adaptive optimization of the learning process, which allows for achieving a target accuracy while minimizing the energy consumption of the learning process.
On the Limit Performance of Floating Gossip
In this paper we investigate the limit performance of Floating Gossip, a new, fully distributed Gossip Learning scheme which relies on Floating Content to implement location-based probabilistic evolution of machine learning models in an infrastructure-less manner.
DeepFloat: Resource-Efficient Dynamic Management of Vehicular Floating Content
Opportunistic communications are expected to playa crucial role in enabling context-aware vehicular services.
Selecting the top-quality item through crowd scoring
We investigate crowdsourcing algorithms for finding the top-quality item within a large collection of objects with unknown intrinsic quality values.
