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Results tagged with bayesian-optimization
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user 33444
For questions related to Bayesian optimization (BO), which is a technique used to model an unknown function (that is expensive to evaluate), based on concepts of a surrogate model (which is usually a Gaussian process, which models the unknown function), Bayesian inference (to update the Gaussian process) and an acquisition function (which guides the Bayesian inference). BO can be used for hyper-parameter optimization.
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Bayesian hyperparameter optimization, is it worth it?
Efficiently integrating HPO frameworks into an existing project is non-trivial. Most common datasets/tasks already have established architectures/hyperparameters/etc. and require only a few additional …
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