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. 1910.05492
  4. Cited By
Multi-objective Evolutionary Algorithms are Still Good: Maximizing
  Monotone Approximately Submodular Minus Modular Functions

Multi-objective Evolutionary Algorithms are Still Good: Maximizing Monotone Approximately Submodular Minus Modular Functions

12 October 2019
Chao Qian
ArXivPDFHTML

Papers citing "Multi-objective Evolutionary Algorithms are Still Good: Maximizing Monotone Approximately Submodular Minus Modular Functions"

2 / 2 papers shown
Title
Peptide Vaccine Design by Evolutionary Multi-Objective Optimization
Peptide Vaccine Design by Evolutionary Multi-Objective Optimization
Dan-Xuan Liu
Yi-Heng Xu
Chao Qian
24
1
0
09 Jun 2024
Result Diversification by Multi-objective Evolutionary Algorithms with
  Theoretical Guarantees
Result Diversification by Multi-objective Evolutionary Algorithms with Theoretical Guarantees
Chao Qian
Danqin Liu
Zhi-Hua Zhou
14
13
0
18 Oct 2021
1