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Hyperband adaptive hyperparameter resource allocation

Contribution grade

Hyperparameter optimization · Human-designed research method or resource

Reference score155,000Provisional editorial estimate of this exact contribution; its grade is assessed separately.

What changed

Runs successive-halving brackets with different breadth/depth allocations, adapting resource spending among configurations instead of requiring a fixed number of candidates.

Scientific scope

Runs successive-halving brackets with different breadth/depth allocations, adapting resource spending among configurations instead of requiring a fixed number of candidates. The controlling v1 has an early title and budget-doubling formulation. Bounds rely on its sampling/loss-limit and uniform convergence-envelope assumptions, not arbitrary misleading learning curves at any fixed budget. Successive halving is inherited; no claim to invent bandit optimization.

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 controlling v1 has an early title and budget-doubling formulation. Bounds rely on its sampling/loss-limit and uniform convergence-envelope assumptions, not arbitrary misleading learning curves at any fixed budget. Successive halving is inherited; no claim to invent bandit optimization.

Contributors

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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