Poblano v1.0 : a Matlab toolbox for gradient-based optimization. Page: 3 of 48
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Printed March 2010
Poblano v1.0: A Matlab Toolbox for Gradient-Based
Daniel M. Dunlavy
Computer Science & Informatics Department
Sandia National Laboratories, Albuquerque, NM 87123-1318
Tamara G. Kolda and Evrim Acar
Information and Decision Sciences Department
Sandia National Laboratories
Livermore, CA 94551-9159
Email: email@example.com, firstname.lastname@example.org
We present Poblano v1.0, a Matlab toolbox for solving gradient-based unconstrained optimization
problems. Poblano implements three optimization methods (nonlinear conjugate gradients, limited-
memory BFGS, and truncated Newton) that require only first order derivative information. In this
paper, we describe the Poblano methods, provide numerous examples on how to use Poblano, and present
results of Poblano used in solving problems from a standard test collection of unconstrained optimization
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Dunlavy, Daniel M.; Acar, Evrim (Sandia National Laboratories, Livermore, CA) & Kolda, Tamara Gibson (Sandia National Laboratories, Livermore, CA). Poblano v1.0 : a Matlab toolbox for gradient-based optimization., report, March 1, 2010; United States. (digital.library.unt.edu/ark:/67531/metadc1012433/m1/3/: accessed December 18, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.