Abstract: In decentralized machine learning over a network of workers, each worker updates its local model as a weighted average of its local model and all models received from its neighbors.
Forbes contributors publish independent expert analyses and insights. Keely founded Making Space, closing the disability employment gap. "One of the most striking takeaways from SYNC25 was how many ...
Abstract: To jointly tackle the challenges of data and node heterogeneity in decentralized learning, we propose a distributed strong lottery ticket hypothesis (DSLTH), based on which a ...
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