Bootstrap Performance Profiles in Stochastic Algorithms Assessment

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2015

Autores

Costa, L (Autor) Outra; Espirito Santo, IACPE (Autor) Outra; oliveira, p (Autor) ICBAS

Ata de Conferência Internacional

Título: PROCEEDINGS OF THE INTERNATIONAL CONFERENCE OF NUMERICAL ANALYSIS AND APPLIED MATHEMATICS 2014 (ICNAAM-2014)

International Conference on Numerical Analysis and Applied Mathematics (ICNAAM)

Rhodes, GREECE, SEP 22-28, 2014

Indexação

ISI Web of Knowledge - 0 Citações

Scopus - 0 Citações

Outras Informações

ID Authenticus: P-00G-BC1

DOI: 10.1063/1.4912429

Abstract (EN): Optimization with stochastic algorithms has become a relevant research field. Due to its stochastic nature, its assessment is not straightforward and involves integrating accuracy and precision. Performance profiles for the mean do not show the trade-off between accuracy and precision, and parametric stochastic profiles require strong distributional assumptions and are limited to the mean performance for a large number of runs. In this work, bootstrap performance profiles are used to compare stochastic algorithms for different statistics. This technique allows the estimation of the sampling distribution of almost any statistic even with small samples. Multiple comparison profiles are presented for more than two algorithms. The advantages and drawbacks of each assessment methodology are discussed.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 4