AWhat changed
Partitioned neural computation across machines and replicas, combining asynchronous Downpour SGD and coordinated distributed batch optimization through sharded parameter storage.
Scientific scope
Partitioned neural computation across machines and replicas, combining asynchronous Downpour SGD and coordinated distributed batch optimization through sharded parameter storage. System/algorithm integration inherits SGD, L-BFGS, Adagrad and earlier distributed optimization, not their invention or first parameter-server concept. Scaling benefits depend on connectivity, resource allocation, communication and staleness; not unconstrained neural convergence or universal speedup.
Evidence
The linked original sources describe the stated contribution and its evidence limits. WRS has not independently rerun the experiments or certified a proof. System/algorithm integration inherits SGD, L-BFGS, Adagrad and earlier distributed optimization, not their invention or first parameter-server concept. Scaling benefits depend on connectivity, resource allocation, communication and staleness; not unconstrained neural convergence or universal speedup.
Contributors
- Source-listed authors and technical contributors · SCIENCE: Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.
Provisional WRS assessment, edition 2026-10-16.1. Independent expert calibration is pending. This grade does not certify correctness or assign ownership.
Full scientific record · Browse contribution grades · Request a correction