Fast solver for some computational imaging problems: A regularized weighted least-squares approach

Recently, we used this standard least squares approximation approach to extend the notion of interaction index for classes of functions dened on the unit hyper-... However, when we

This approach is based on the use of original weighted least-squares criteria: as opposed to other existing methods, it requires no dithering signal and it

Le but de tous ces efforts est de comparer des algorithmes entre eux (lequel est le plus efficace ?) ou bien des problèmes entre eux (lequel est le plus difficile ?).. Pour que

Approximation of null controls for semilinear heat equations using a least-squares approach.. Jérôme Lemoine, Irene Marín-Gayte,

In this paper we proposed m-power regularized least squares regression (RLSR), a supervised regression algorithm based on a regularization raised to the power of m, where m is with

The method, based on a least-squares approach, generalizes Newton type methods and guarantees the convergence whatever be the initial element of the sequence..

This document is an introduction to the Matlab package SDLS (Semi-Definite Least-Squares) for solving least-squares problems over convex symmetric cones.. The package is

We prove existence of solutions in various ways, provide a characterization of solutions in terms of nonlinear systems, and illustrate the applicability of results as a