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BOHB model-based Hyperband optimization

Contribution grade

Hyperparameter optimization · Human-designed research method or resource

Reference score130,000Provisional editorial estimate of this exact contribution; its grade is assessed separately.

What changed

Combines Hyperband's multi-fidelity allocation with multidimensional density-estimation guidance, using the largest sufficiently populated budget model and retaining random exploration.

Scientific scope

Combines Hyperband's multi-fidelity allocation with multidimensional density-estimation guidance, using the largest sufficiently populated budget model and retaining random exploration. It reuses Hyperband/TPE ideas; low-fidelity rankings can mislead and a fixed positive random-sampling fraction underlies the asymptotic fallback argument. Empirical anytime gains do not certify a finite-budget global optimum.

Evidence

The linked original sources describe the stated contribution and its evidence limits. WRS has not independently rerun the experiments or certified a proof. It reuses Hyperband/TPE ideas; low-fidelity rankings can mislead and a fixed positive random-sampling fraction underlies the asymptotic fallback argument. Empirical anytime gains do not certify a finite-budget global optimum.

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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