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Pareto Optimization for Subset Selection with Dynamic Partition Matroid
  Constraints

Pareto Optimization for Subset Selection with Dynamic Partition Matroid Constraints

AAAI Conference on Artificial Intelligence (AAAI), 2020
16 December 2020
A. Do
Frank Neumann
ArXiv (abs)PDFHTML

Papers citing "Pareto Optimization for Subset Selection with Dynamic Partition Matroid Constraints"

5 / 5 papers shown
Biased Pareto Optimization for Subset Selection with Dynamic Cost
  Constraints
Biased Pareto Optimization for Subset Selection with Dynamic Cost Constraints
Dan-Xuan Liu
Chao Qian
207
1
0
18 Jun 2024
Benchmarking Algorithms for Submodular Optimization Problems Using
  IOHProfiler
Benchmarking Algorithms for Submodular Optimization Problems Using IOHProfilerIEEE Congress on Evolutionary Computation (CEC), 2023
Frank Neumann
Aneta Neumann
Chao Qian
Viet Anh Do
Jacob De Nobel
Diederick Vermetten
Saba Sadeghi Ahouei
Furong Ye
Hongya Wang
Thomas Bäck
244
6
0
02 Feb 2023
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 Zhou
226
19
0
18 Oct 2021
Multi-objective Evolutionary Algorithms are Generally Good: Maximizing
  Monotone Submodular Functions over Sequences
Multi-objective Evolutionary Algorithms are Generally Good: Maximizing Monotone Submodular Functions over SequencesTheoretical Computer Science (TCS), 2021
Chao Qian
Danyang Liu
Chao Feng
Shengcai Liu
247
14
0
20 Apr 2021
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 FunctionsEvolutionary Computation (Evol. Comput.), 2019
Chao Qian
257
25
0
12 Oct 2019
1
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