ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1809.05450
  4. Cited By
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

14 September 2018
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
78
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
57
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
77
31
0
09 Nov 2018
1