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NTIRE 2017 Challenge on Single Image Super-Resolution ...

aeirikur@vision.ee.ethz.ch Radu Timofte CVL, ETH Zurich & Merantix GmbH radu.timofte@vision.ee.ethz.ch Abstract This paper introduces a novel large dataset for example-based single image super-resolution and studies the state-of-the-art as emerged from the NTIRE 2017 challenge. The challenge is the rst challenge of its kind, with 6 compe-

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298 Chapter 11. Nonlinear Optimization Examples The NLPNMS and NLPQN subroutines permit nonlinear constraints on parameters. For problems with nonlinear constraints, these subroutines do not use a feasible-point method; instead, the algorithms begin with whatever starting point you specify, whether feasible or infeasible.

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The best-known kind of optimization model, which has served for all of our examples so far, is the linear program. The variables of a linear program take values from some continuous range; the objective and constraints must use only linear functions of the vari-ables. Previous chapters have described these requirements informally or implicitly ...

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exception of the Problems, no changes have been made to Chapter 11. A ‘‘Quick Overview’’ section has been added to Chapter 12 discussing capacity-approaching codes, run-length codes, and digital television. A feature of the later editions of Principles of Communications was the inclusion of several computer examples within each chapter.

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powerful mechanism for solving equations and for optimization. On the other hand, even very simple non-convergent nonlinear iterative systems may admit remarkably complex, chaotic behavior. The third section is devoted to basic solution techniques for nonlinear equations and nonlinear systems, and includes bisection, general iteration, and the very

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Convex Optimization - Stanford University

Preface This book is about convex optimization, a special class of mathematical optimiza-tion problems, which includes least-squares and linear programming problems.

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Introduction to Applied Linear Algebra

Preface This book is meant to provide an introduction to vectors, matrices, and least squares methods, basic topics in applied linear algebra. Our goal is to give the

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