ResearchTrend.AI
User preferences in Bayesian multi-objective optimization: the expected weighted hypervolume improvement criterion

User preferences in Bayesian multi-objective optimization: the expected weighted hypervolume improvement criterion

Paul Feliot
Julien Bect
E. Vázquez
ArXiv (abs)PDFHTML

Papers citing "User preferences in Bayesian multi-objective optimization: the expected weighted hypervolume improvement criterion"

4 / 4 papers shown
Title
Preference Exploration for Efficient Bayesian Optimization with Multiple Outcomes
Preference Exploration for Efficient Bayesian Optimization with Multiple Outcomes
Zhiyuan Jerry Lin
Raul Astudillo
P. Frazier
E. Bakshy
75
38
0
21 Mar 2022
Learning Arbitrary Quantities of Interest from Expensive Black-Box Functions through Bayesian Sequential Optimal Design
Learning Arbitrary Quantities of Interest from Expensive Black-Box Functions through Bayesian Sequential Optimal Design
Piyush Pandita
Nimish Awalgaonkar
Ilias Bilionis
Jitesh H. Panchal
55
1
0
16 Dec 2019
Multi-Attribute Bayesian Optimization With Interactive Preference Learning
Multi-Attribute Bayesian Optimization With Interactive Preference Learning
Raul Astudillo
P. Frazier
72
33
0
14 Nov 2019
Targeting Solutions in Bayesian Multi-Objective Optimization: Sequential and Batch Versions
Targeting Solutions in Bayesian Multi-Objective Optimization: Sequential and Batch Versions
David Gaudrie
Rodolphe Le Riche
Victor Picheny
B. Enaux
V. Herbert
75
31
0
09 Nov 2018