Expected Improvements for the Asynchronous Parallel Global Optimization of Expensive Functions : Potentials and Challenges - Archive ouverte HAL Access content directly
Journal Articles Lecture Notes in Computer Science Year : 2012

Expected Improvements for the Asynchronous Parallel Global Optimization of Expensive Functions : Potentials and Challenges

(1, 2) , (1, 3, 2, 4, 5, 6) , (7) ,
1
2
3
4
5
6
7

Abstract

Sequential sampling strategies based on Gaussian processes are now widely used for the optimization of problems involving costly simulations. But Gaussian processes can also generate parallel optimiza- tion strategies. We focus here on a new, parameter free, parallel expected improvement criterion for asynchronous optimization. An estimation of the criterion, which mixes Monte Carlo sampling and analytical bounds, is proposed. Logarithmic speed-ups are measured on 1 and 9 dimensional functions.
Not file

Dates and versions

emse-00686504 , version 1 (10-04-2012)

Identifiers

Cite

Janis Janusevskis, Rodolphe Le Riche, David Ginsbourger, Ramunas Girdziusas. Expected Improvements for the Asynchronous Parallel Global Optimization of Expensive Functions : Potentials and Challenges. Lecture Notes in Computer Science, 2012, Learning and Intelligent Optimization, pp. 413-418. ⟨10.1007/978-3-642-34413-8_37⟩. ⟨emse-00686504⟩
73 View
0 Download

Altmetric

Share

Gmail Facebook Twitter LinkedIn More