Maximizing Submodular or Monotone Functions under Partition Matroid
Constraints by Multi-objective Evolutionary Algorithms

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Maximizing Submodular or Monotone Functions under Partition Matroid Constraints by Multi-objective Evolutionary Algorithms

23 June 2020

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Papers citing "Maximizing Submodular or Monotone Functions under Partition Matroid Constraints by Multi-objective Evolutionary Algorithms"

7 / 7 papers shown

Title
Evolving Reliable Differentiating Constraints for the Chance-constrained Maximum Coverage Problem Saba Sadeghi Ahouei Jacob De Nobel Aneta Neumann Thomas Bäck Frank Neumann AI4TS 60 4 0 29 May 2024
Rigorous Runtime Analysis of MOEA/D for Solving Multi-Objective Minimum Weight Base Problems A. Do Aneta Neumann Frank Neumann Andrew M. Sutton 108 12 0 06 Jun 2023
Benchmarking Algorithms for Submodular Optimization Problems Using IOHProfiler Frank Neumann Aneta Neumann Chao Qian Viet Anh Do Jacob De Nobel Diederick Vermetten Saba Sadeghi Ahouei Furong Ye Hongya Wang Thomas Bäck 69 5 0 02 Feb 2023
Effective and Imperceptible Adversarial Textual Attack via Multi-objectivization Shengcai Liu Ning Lu W. Hong Chao Qian Ke Tang AAML 102 15 0 02 Nov 2021
Multi-objective Evolutionary Algorithms are Generally Good: Maximizing Monotone Submodular Functions over Sequences Chao Qian Danyang Liu Chao Feng K. Tang 51 13 0 20 Apr 2021
Pareto Optimization for Subset Selection with Dynamic Partition Matroid Constraints A. Do Frank Neumann 63 8 0 16 Dec 2020
A Survey on Recent Progress in the Theory of Evolutionary Algorithms for Discrete Optimization Benjamin Doerr Frank Neumann 64 34 0 30 Jun 2020