Results 261 to 270 of about 8,591 (298)
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Adaptive Greedy Approximations
Constructive Approximation, 1997Let \({\mathcal H}\) be a Hilbert space. A dictionary \({\mathcal D}\) for \({\mathcal H}\) is a family of unit vectors in \({\mathcal H}\) such that finite linear combinations of \(g_{\gamma }\in {\mathcal D}\) are dense in \({\mathcal H}\). The problem of approximations over a dictionary is studied from different points.
Davis, G., Mallat, S., Avellaneda, M.
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A greedy approximation for minimum connected dominating sets
Theoretical Computer Science, 2004 Given a graph, a connected dominating set is a subset of vertices such that every vertex is either in the subset or adjacent to a vertex in the subset and the subgraph induced by the subset is connected.
Lu Ruan, Hongwei Du, Xiaohua Jia
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Acta Numerica, 2006
In this survey we discuss properties of specific methods of approximation that belong to a family of greedy approximation methods (greedy algorithms). It is now well understood that we need to study nonlinear sparse representations in order to significantly increase our ability to process (compress, denoise,etc.) large data sets. Sparse representations
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In this survey we discuss properties of specific methods of approximation that belong to a family of greedy approximation methods (greedy algorithms). It is now well understood that we need to study nonlinear sparse representations in order to significantly increase our ability to process (compress, denoise,etc.) large data sets. Sparse representations
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Greedy approximation algorithms for directed multicuts
Networks, 2005AbstractThe Directed Multicut (DM) problem is: given a simple directed graph G = (V, E) with positive capacities ue on the edges, and a set K ⊆ V × V of ordered pairs of nodes of G, find a minimum capacity K‐multicut; C ⊆ E is a K‐multicut if in G − C there is no (s, t)‐path for any (s, t) ⫅ K.
Yana Kortsarts, Guy Kortsarz, Zeev Nutov
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Generalized Approximate Weak Greedy Algorithms
Mathematical Notes, 2005The authors discuss so-called ``generalized approximate weak greedy algorithms'' (gAWGAs) in a Hilbert space, which describe the process of greedy expansions involving errors in calculation of the coefficients in terms of their absolut values. The concepts of ``dictionary'' in a real Hilbert space with inner product and of the ``gAWGA-expansion of an ...
Galatenko, V. V., Livshits, E. D.
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An approximation to the greedy algorithm for differential compression
IBM Journal of Research and Development, 2006We present a new differential compression algorithm that combines the hash value techniques and suffix array techniques of previous work. The term "differential compression" refers to encoding a file (a version file) as a set of changes with respect to another file (a reference file).
Ramesh C. Agarwal +3 more
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Relaxation in Greedy Approximation
Constructive Approximation, 2007We study greedy algorithms in a Banach space from the point of view of convergence and rate of convergence. There are two well-studied approximation methods: the Weak Chebyshev Greedy Algorithm (WCGA) and the Weak Relaxed Greedy Algorithm (WRGA). The WRGA is simpler than the WCGA in the sense of computational complexity.
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Two Lower Estimates in Greedy Approximation
Constructive Approximation, 2003Given an arbitrary Hilbert space with a denumerable orthonormal basis, the authors construct two examples providing lower estimates for the rate of convergence of the pure Greedy algorithm and of the weak Greedy algorithm, respectively.
Livshitz, E. D., Temlyakov, V. N.
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2011
This first book on greedy approximation gives a systematic presentation of the fundamental results. It also contains an introduction to two hot topics in numerical mathematics: learning theory and compressed sensing. Nonlinear approximation is becoming increasingly important, especially since two types are frequently employed in applications: adaptive ...
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This first book on greedy approximation gives a systematic presentation of the fundamental results. It also contains an introduction to two hot topics in numerical mathematics: learning theory and compressed sensing. Nonlinear approximation is becoming increasingly important, especially since two types are frequently employed in applications: adaptive ...
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A greedy approximation algorithm for minimum-gap scheduling
Journal of Scheduling, 2013zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Marek Chrobak +5 more
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