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. 2110.11070
  4. Cited By
A Nested Weighted Tchebycheff Multi-Objective Bayesian Optimization
  Approach for Flexibility of Unknown Utopia Estimation in Expensive Black-box
  Design Problems

A Nested Weighted Tchebycheff Multi-Objective Bayesian Optimization Approach for Flexibility of Unknown Utopia Estimation in Expensive Black-box Design Problems

16 October 2021
Arpan Biswas
Claudio Fuentes
C. Hoyle
ArXiv (abs)PDFHTML

Papers citing "A Nested Weighted Tchebycheff Multi-Objective Bayesian Optimization Approach for Flexibility of Unknown Utopia Estimation in Expensive Black-box Design Problems"

2 / 2 papers shown
Title
Unraveling the Versatility and Impact of Multi-Objective Optimization:
  Algorithms, Applications, and Trends for Solving Complex Real-World Problems
Unraveling the Versatility and Impact of Multi-Objective Optimization: Algorithms, Applications, and Trends for Solving Complex Real-World Problems
Noor A. Rashed
Yossra H. Ali
Tarik A. Rashid
A. Salih
135
2
0
29 Jun 2024
A dynamic Bayesian optimized active recommender system for
  curiosity-driven Human-in-the-loop automated experiments
A dynamic Bayesian optimized active recommender system for curiosity-driven Human-in-the-loop automated experiments
Arpan Biswas
Yongtao Liu
Nicole Creange
Yu-Chen Liu
S. Jesse
Jan-Chi Yang
Sergei V. Kalinin
M. Ziatdinov
Rama K Vasudevan
98
5
0
05 Apr 2023
1