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Greedy Approximation Algorithms
2013Greedy strategy is a simple and natural method in the design of approximation algorithms. This chapter presents greedy approximation algorithms for very broad classes of maximization problems and minimization problems and analyzes their approximation bounds.
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1999
In this chapter we study a method for optimizing over certain set systems, the so-called greedy algorithm. More precisely, it is used for maximizing a weight function on so-called independence systems, the classical instance being the system of spanning forests of a graph.
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In this chapter we study a method for optimizing over certain set systems, the so-called greedy algorithm. More precisely, it is used for maximizing a weight function on so-called independence systems, the classical instance being the system of spanning forests of a graph.
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2001
In a separable Hilbert space $\cal H$, greedy algorithms iteratively define $m$-term approximants to a given vector $f$ from a complete redundant dictionary $\cal D$. With very large dictionaries, the pure greedy algorithm cannot be implemented and must be replaced with a weak greedy algorithm which is defined through a weakness sequence $t_m \in [0,1],
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In a separable Hilbert space $\cal H$, greedy algorithms iteratively define $m$-term approximants to a given vector $f$ from a complete redundant dictionary $\cal D$. With very large dictionaries, the pure greedy algorithm cannot be implemented and must be replaced with a weak greedy algorithm which is defined through a weakness sequence $t_m \in [0,1],
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