Group fairness in non-monotone submodular maximization

Maximizing a submodular function has a wide range of applications in machine learning and data mining. One such application is data summarization whose goal is to select a small set of representative and diverse data items from a large dataset. However, data items might have sensitive attributes suc...

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Veröffentlicht in:	Journal of combinatorial optimization Jg. 45; H. 3; S. 88
Hauptverfasser:	Yuan, Jing, Tang, Shaojie
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.04.2023 Springer Nature B.V
Schlagworte:	Algorithms Approximation Combinatorics Constraints Convex and Discrete Geometry Data mining Decision making Feature selection Machine learning Mathematical Modeling and Industrial Mathematics Mathematics Mathematics and Statistics Maximization Operations Research/Decision Theory Optimization S.I. : AAIM 2022 Theory of Computation Utility functions Approximation algorithm Submodular optimization Group fairness
ISSN:	1382-6905, 1573-2886
Online-Zugang:	Volltext
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