2 Learning Rule Optimization

Due to the discrete nature of the charge carriers, the current presents some fluctuations (noise) known as shot noise , which we aim to characterize here (not to be confused with

Here, our MI-Spearmint variant of the Gaussian- process-based SMBO method Spearmint [29] (a state-of-the-art ap- proach for low-dimensional hyperparameter optimization) yielded

While the intuition that a morphological transform’s salience should be based on the number of types it applies to is correct, the large number of foreign and misspelled words in

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Path planning, Additive manufacturing, Laser based powder bed fusion, Electron beam powder bed fusion, Shape

Further applications presented in Section 6 are the minimization of eigenvalues of the Dirichlet-Laplace operator under convexity and constant width constraints, approxima- tion

In this paper we present a methodology to optimize several hyper- parameters, based on the computation of the gradient of a model selection criterion with respect to

Further applications presented in Section 6 concern the minimization of eigenvalues of the Dirichlet-Laplace operator under convexity and constant width constraints, approximation