Applied Deep Learning with TensorFlow 2 by Umberto Michelucci

Author:Umberto Michelucci
Language: eng
Format: epub
ISBN: 9781484280201
Publisher: Apress

If you are interested in a very good paper on the random search scale at high-dimensional problems, you can read the paper by J. Bergstra and Y. Bengio, “Random Search for Hyper-Parameter Optimization” [1].

Coarse to Fine Optimization

There is still an optimization trick that helps with grid or random search. It is called “coarse to fine optimization .” Let’s suppose we want to find the maximum of f(x) between xmin and xmax. We will look at the idea for random search, but it works in the same way as with grid search. The following steps give you the algorithm you need to follow.1.

Do a random search in the region R1 = (xmin, xmax). Indicate the maximum found with (x1, f1).

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