What is recorded here?
Models promising versus remaining conditional configurations with density estimators and expected-improvement selection; Hyperopt packages structured stochastic search spaces, interchangeable optimizers and persistent asynchronous trials.
Source-linked catalogue note. A detailed explanatory guide has not yet been prepared for this entry.
Scientific scope
Related algorithm/library lineage bundled with distinct four/three-author source bylines. TPE's density factorization limits modeling of parameter interactions; selected candidates approximate acquisition maximization. Hyperopt2013offers random search/TPE while other optimizers are future work. Parallelism trades per-evaluation efficiency for wall time; no global finite-budget guarantee.
Read the original work
- Algorithms for Hyper-Parameter Optimization
- Hyperopt: A Python Library for Optimizing the Hyperparameters of Machine Learning Algorithms
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People and systems
James Bergstra; Rémi Bardenet; Yoshua Bengio; Balázs Kégl; Dan Yamins; David D. Cox
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.
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English catalogue narrative
Tree-structured Parzen estimators and Hyperopt
Models promising versus remaining conditional configurations with density estimators and expected-improvement selection; Hyperopt packages structured stochastic search spaces, interchangeable optimizers and persistent asynchronous trials.
Scientific scope
Related algorithm/library lineage bundled with distinct four/three-author source bylines. TPE's density factorization limits modeling of parameter interactions; selected candidates approximate acquisition maximization. Hyperopt2013offers random search/TPE while other optimizers are future work. Parallelism trades per-evaluation efficiency for wall time; no global finite-budget guarantee.
Reading status
This is a source-linked WRS catalogue note. A full explanatory guide and independent scientific reconstruction have not been completed for this entry. Read the identified original work for its complete narrative and arguments.
People and systems
James Bergstra; Rémi Bardenet; Yoshua Bengio; Balázs Kégl; Dan Yamins; David D. Cox
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.