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This paper is devoted to theoretical aspects on optimality of sparse approximation. We undertake a quantitative study of new types of greedy-like bases that have recently arisen in the context of nonlinear $m$-term approximation in Banach…

Functional Analysis · Mathematics 2022-05-20 Fernando Albiac , Jose L. Ansorena , Miguel Berasategui

Recently, it has been discovered that results on universal sampling discretization of the square norm are useful in sparse sampling recovery with error being measured in the square norm. It was established that a simple greedy type…

Numerical Analysis · Mathematics 2023-07-11 F. Dai , V. Temlyakov

Let $X$ be a Banach space and $(e_n)_{n=1}^\infty$ be a basis. For a function $f$ in a large collection $\mathcal{F}$ (closed under composition), we define and characterize $f$-greedy and $f$-almost greedy bases. We study relations among…

Functional Analysis · Mathematics 2023-05-16 Hung Viet Chu

We introduce and study the notion of weak semi-greedy systems -which is inspired in the concepts of semi-greedy and Branch semi-greedy systems and weak thresholding sets-, and prove that in the context Markushevich bases in infinite…

Functional Analysis · Mathematics 2021-10-15 Miguel Berasategui , Silvia Lassalle

In this paper we study a new class of bases, weaker than quasi-greedy bases, which retain their unconditionality properties and can provide the same optimality for the thresholding greedy algorithm. We measure how far these bases are from…

Functional Analysis · Mathematics 2021-06-03 Fernando Albiac , Jose L. Ansorena , Miguel Berasategui , Pablo M. Berna , Silvia Lassalle

The rate of convergence of the classical Thresholding Greedy Algorithm with respect to bases is studied in this paper. We bound the error of approximation by the product of both norms -- the norm of $f$ and the $A_1$-norm of $f$. We obtain…

Numerical Analysis · Mathematics 2024-07-29 V. N. Temlyakov

The aim of this article is to use Banach lattice techniques to study coordinate systems in function spaces. We begin by proving that the greedy algorithm of a basis is order convergent if and only if a certain maximal inequality is…

Functional Analysis · Mathematics 2026-01-06 Pablo Berná , Daniel Freeman , Timur Oikhberg , Mitchell Taylor

The purpose of this paper is to introduce $\omega$-Chebyshev-greedy and $\omega$-partially greedy approximation classes and to study their relation with $\omega$-approximation spaces, where the latter are a generalization of the classical…

Functional Analysis · Mathematics 2023-03-17 Pablo M. Berná , Hung Viet Chu , Eugenio Hernández

The goal of this paper is to study the performance of the Thresholding Greedy Algorithm (TGA) when we increase the size of greedy sums by a constant factor $\lambda\geqslant 1$. We introduce the so-called $\lambda$-almost greedy and…

Functional Analysis · Mathematics 2023-02-13 Hung Viet Chu

We shall present a new characterization of greedy bases and 1-greedy bases in terms of certain functionals defined using distances to one dimensional subspaces generated by the basis. We also introduce a new property that unifies the…

Functional Analysis · Mathematics 2016-04-26 Pablo M. Berná , Óscar Blasco

Given a Banach space X and one of its compact sets F, we consider the problem of finding a good n dimensional space X_n \subset X which can be used to approximate the elements of F. The best possible error we can achieve for such an…

Functional Analysis · Mathematics 2012-04-12 Ronald DeVore , Guergana Petrova , Przemyslaw Wojtaszczyk

We compute the right and left democracy functions of admissible wavelet bases in variable Lebesgue spaces defined on $R^n$. As an application we give Lebesgue type inequalities for these wavelet bases. We also show that our techniques can…

Functional Analysis · Mathematics 2018-10-10 David Cruz-Uribe , SFO , Eugenio Hernández , José María Martell

We describe a greedy algorithm that approximates the Carleson constant of a collection of general sets. The approximation has a logarithmic loss in a general setting, but is optimal up to a constant with only mild geometric assumptions. The…

Classical Analysis and ODEs · Mathematics 2022-02-22 Guillermo Rey

In many prediction problems, it is not uncommon that the number of variables used to construct a forecast is of the same order of magnitude as the sample size, if not larger. We then face the problem of constructing a prediction in the…

Statistics Theory · Mathematics 2016-02-08 Alessio Sancetta

Considering the set cover problem, by modifying the approach that gives a logarithmic approximation guarantee for the greedy algorithm, we obtain an estimation of the greedy algorithm's accuracy for a particular input. We compare the…

Data Structures and Algorithms · Computer Science 2019-02-13 Alexander Prolubnikov

We study moment rearrangement invariant spaces, which contain as particular cases the generalized Grand Lebesgue Spaces, and provide norm estimates for some operators, not necessarily linear, acting between some measurable rearrangement…

Functional Analysis · Mathematics 2022-12-26 M. R. Formica , E. Ostrovsky , L. Sirota

We prove some results on the rate of convergence of greedy algorithms, which provide expansions. We consider both the case of Hilbert spaces and the more general case of Banach spaces. The new ingredient of the paper is that we bound the…

Numerical Analysis · Mathematics 2023-04-14 V. N. Temlyakov

We study sparse approximation by greedy algorithms. Our contribution is two-fold. First, we prove exact recovery with high probability of random $K$-sparse signals within $\lceil K(1+\e)\rceil$ iterations of the Orthogonal Matching Pursuit…

Numerical Analysis · Mathematics 2013-04-03 Eugene Livshitz , Vladimir Temlyakov

It is a survey on recent results in constructive sparse approximation. Three directions are discussed here: (1) Lebesgue-type inequalities for greedy algorithms with respect to a special class of dictionaries, (2) constructive sparse…

Numerical Analysis · Mathematics 2015-11-06 Vladimir Temlyakov

In this paper, we study weights for the Thresholding Greedy Algorithm (TGA). While previous work focused on sequential weights $\varsigma = (s_n)_{n\in\mathbb{N}}$ on each positive integer, we study a more general weight $\omega =…

Functional Analysis · Mathematics 2023-02-10 Hung Viet Chu