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Bibliographic Details
Main Author: García, Andrea
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2408.08935
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author García, Andrea
author_facet García, Andrea
contents Greedy algorithms are a fundamental category of algorithms in mathematics and computer science, characterized by their iterative, locally optimal decision-making approach, which aims to find global optima. In this review, we will discuss two greedy algorithms. First, we will talk about the so-called Relaxed Greedy Algorithm in the context of dictionaries in Hilbert spaces analyzing the optimality of definition of this algorithm and, next, we give a general overview of the Thresholding Greedy Algorithm and the Chebyshev Thresholding Greedy Algorithm with regard to bases in p-Banach spaces with $0 < p \leq 1$. In both cases, we pose some questions for future research.
format Preprint
id arxiv_https___arxiv_org_abs_2408_08935
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Greedy algorithms: a review and open problems
García, Andrea
Functional Analysis
Greedy algorithms are a fundamental category of algorithms in mathematics and computer science, characterized by their iterative, locally optimal decision-making approach, which aims to find global optima. In this review, we will discuss two greedy algorithms. First, we will talk about the so-called Relaxed Greedy Algorithm in the context of dictionaries in Hilbert spaces analyzing the optimality of definition of this algorithm and, next, we give a general overview of the Thresholding Greedy Algorithm and the Chebyshev Thresholding Greedy Algorithm with regard to bases in p-Banach spaces with $0 < p \leq 1$. In both cases, we pose some questions for future research.
title Greedy algorithms: a review and open problems
topic Functional Analysis
url https://arxiv.org/abs/2408.08935