In this paper a new approach for obtaining an approximation global optimum solution of zero-one nonlinear programming (0-1 NP) problem which we call it Parametric Linearization Approach (P.L.A) is ...
Abstract: The purpose of this article is to present the Parametric Minimum Error Entropy (PMEE) principle and to show a case study of the proposed criterion in a ...
Abstract: The paper is concerned with parametric identification algorithm for a linear dynamic control object when a priori information about the object is no fully available. In this paper the ...
Neural Modules with Adaptive Nonlinear Constraints and Efficient Regularizations (NeuroMANCER) is an open-source differentiable programming (DP) library for solving parametric constrained optimization ...
Repository for the course Calcolo Scientifico for Scienze Matematiche per l'Intelligenza Artificiale
1.3 Introduction to functional analysis PDF html md 2 Elliptic problems 2.1 Elliptic problems PDF html md 2.2 Finite differences for elliptic problems PDF html md 2.3 Finite elements for elliptic ...
This paper proposes two new classes of estimators for regression models fitted to survey data. The proposed estimators account for the effect of nonignorable sampling schemes which are known to bias ...
In this article, we revisit some problems in non-parametric hypothesis testing. First, we extend the classical result of Bahadur & Savage [Ann. Math. Statist. 25 (1956) 1115] to other testing problems ...
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