Greedy algorithms: a review and open problems

Greedy algorithms are a fundamental class of mathematics and computer science algorithms, defined by their iterative approach of making locally optimal decisions to approximate global optima. In this review, we focus on two greedy algorithms. First, we examine the relaxed greedy algorithm in the con...

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Veröffentlicht in:Journal of inequalities and applications Jg. 2025; H. 1; S. 11 - 22
1. Verfasser: García, Andrea
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Cham Springer International Publishing 03.02.2025
Springer Nature B.V
SpringerOpen
Schlagworte:
Algorithms
Analysis
Applications of Mathematics
Approximation
Banach spaces
Chebyshev approximation
Computer science
Data compression
Dictionaries
Greedy algorithm
Greedy algorithms
Greedy bases
Hilbert space
Mathematics
Mathematics and Statistics
Optimization
Review
Greedy algorithm
Greedy bases
41A46
46B15
41A65
ISSN:1029-242X, 1025-5834, 1029-242X
Online-Zugang:Volltext
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Zusammenfassung:Greedy algorithms are a fundamental class of mathematics and computer science algorithms, defined by their iterative approach of making locally optimal decisions to approximate global optima. In this review, we focus on two greedy algorithms. First, we examine the relaxed greedy algorithm in the context of dictionaries in Hilbert spaces, analyzing the optimality of the definition of this algorithm. Next, we provide a general overview of the thresholding greedy algorithm and the Chebyshev thresholding greedy algorithm, with particular attention to their applications to bases in p -Banach spaces with 0 < p ≤ 1 . In both cases, we conclude by posing several questions for future research.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1029-242X
1025-5834
1029-242X
DOI:10.1186/s13660-025-03254-1