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Greedy algorithms: a review and open problems
by
García, Andrea
in
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
2025
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Greedy algorithms: a review and open problems
by
García, Andrea
in
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
2025
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Do you wish to request the book?
Greedy algorithms: a review and open problems
by
García, Andrea
in
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
2025
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Journal Article
Greedy algorithms: a review and open problems
2025
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Overview
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.
Publisher
Springer International Publishing,Springer Nature B.V,SpringerOpen
Subject
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