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Results tagged with bayesian-optimization
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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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Is it normal to see oscillations in tested hyperparameters during bayesian optimisation?
I've been trying out bayesian hyperparameter optimisation (with TPE) on a simple CNN applied to the MNIST handwritten digit dataset. I noticed that over iterations of the optimisation loop, the tested …
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