Assessment of Surrogate Model Settings Using Landscape Analysis

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F20%3A00533901" target="_blank" >RIV/67985807:_____/20:00533901 - isvavai.cz</a>

Result on the web

<a href="http://ceur-ws.org/Vol-2718/paper20.pdf" target="_blank" >http://ceur-ws.org/Vol-2718/paper20.pdf</a>

DOI - Digital Object Identifier

—

Result language

angličtina

Original language name

Assessment of Surrogate Model Settings Using Landscape Analysis

Original language description

This work in progress concerns assessment of surrogate model settings for expensive black-box optimization. The assessment is performed in the context of Gaussian process models used in the Doubly Trained Surrogate (DTS) variant of the state-of-the-art black-box optimizer, the Covariance Matrix Adaptation Evolution Strategy (CMA-ES). This work focuses on the connection between Gaussian process surrogate model predictive accuracy and an essential model hyper-parameter – the covariance function. The performance of DTS-CMA-ES is related to the results of landscape analysis of the objective function. To this end various classification and regression methods are used, proposed in the traditional framework for algorithm selection by Rice. Several single-label classification, multi-label classification, and regression methods are experimentally evaluated on data from DTS-CMAES runs on the noiseless benchmark functions from the COCO platform for comparing continuous optimizers in black-box settings.n

Czech name

—

Czech description

—

Type

D - Article in proceedings

CEP classification

—

OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

<a href="/en/project/GA18-18080S" target="_blank" >GA18-18080S: Fusion-Based Knowledge Discovery in Human Activity Data</a><br>

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2020

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Proceedings of the 20th Conference Information Technologies - Applications and Theory

ISBN

—

ISSN

1613-0073

e-ISSN

—

Number of pages

9

Pages from-to

81-89

Publisher name

Technical University & CreateSpace Independent Publishing

Place of publication

Aachen

Event location

Oravská Lesná

Event date

Sep 18, 2020

Type of event by nationality

EUR - Evropská akce

UT code for WoS article

—