AWhat changed
Trains a shared-weight network progressively over kernel size, depth, width and resolution, then selects subnetworks for multiple deployment constraints without separately training each from scratch.
Scientific scope
Trains a shared-weight network progressively over kernel size, depth, width and resolution, then selects subnetworks for multiple deployment constraints without separately training each from scratch. The O(1) training claim is relative to deployment-scenario count after one expensive supported-space training; per-device search/evaluation and hardware measurements still cost resources. Accuracy equivalence to independent training is empirical, not a theorem over all 10^19 subnetworks.
Evidence
The linked original sources describe the stated contribution and its evidence limits. WRS has not independently rerun the experiments or certified a proof. The O(1) training claim is relative to deployment-scenario count after one expensive supported-space training; per-device search/evaluation and hardware measurements still cost resources. Accuracy equivalence to independent training is empirical, not a theorem over all 10^19 subnetworks.
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.
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