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This paper concerns parameterized convex infinite (or semi-infinite) inequality systems whose decision variables run over general infinite-dimensional Banach (resp. finite-dimensional) spaces and that are indexed by an arbitrary fixed set T…

Optimization and Control · Mathematics 2011-02-07 M. J. CÁnovas , M. A. LÓpez , B. S. Mordukhovich , J. Parra

We propose and analyze batch greedy heuristics for cardinality constrained maximization of non-submodular non-decreasing set functions. We consider the standard greedy paradigm, along with its distributed greedy and stochastic greedy…

Optimization and Control · Mathematics 2021-08-12 Jayanth Jagalur-Mohan , Youssef Marzouk

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

We continue our study of the Thresholding Greedy Algorithm when we restrict the vectors involved in our approximations so that they either are supported on intervals of $\mathbb N$ or have constant coefficients. We introduce and…

Functional Analysis · Mathematics 2023-02-14 Miguel Berasategui , Pablo M. Berná , Hung Viet Chu

For a conditional quasi-greedy basis $\mathcal{B}$ in a Banach space the associated conditionality constants $k_{m}[\mathcal{B}]$ verify the estimate $k_{m}[\mathcal{B}]=\mathcal{O}(\log m)$. Answering a question raised by Temlyakov, Yang,…

Functional Analysis · Mathematics 2017-02-22 Fernando Albiac , José L. Ansorena , Przemysław Wojtaszczyk

We investigate the problem of improving the greedy-type constant of a basis by means of an equivalent renorming of the ambient Banach space. Our main result shows that if a Banach space admits an unconditional and bidemocratic basis whose…

Functional Analysis · Mathematics 2026-03-24 Fernando Albiac , José L. Ansorena , Miguel Berasategui , Pablo M. Berná

Partially greedy bases in Banach spaces were introduced by Dilworth et al. as a strictly weaker notion than the (almost) greedy bases. In this paper, we study two natural ways to strengthen the definition of partial greediness. The first…

Functional Analysis · Mathematics 2023-02-07 Miguel Berasategui , Pablo M. Berná , Hung Viet Chu

The reduced basis method (RBM) empowers repeated and rapid evaluation of parametrized partial differential equations through an offline-online decomposition, a.k.a. a learning-execution process. A key feature of the method is a greedy…

Numerical Analysis · Mathematics 2020-09-16 Jiahua Jiang , Yanlai Chen

In the context of Gaussian conditioning, greedy algorithms iteratively select the most informative measurements, given an observed Gaussian random variable. However, the convergence analysis for conditioning Gaussian random variables…

Statistics Theory · Mathematics 2025-02-18 Daniel Winkle , Ingo Steinwart , Bernard Haasdonk

We study sparse approximation by greedy algorithms. We prove the Lebesgue-type inequalities for the Weak Chebyshev Greedy Algorithm (WCGA), a generalization of the Weak Orthogonal Matching Pursuit to the case of a Banach space. The main…

Machine Learning · Statistics 2013-03-28 Vladimir Temlyakov

We continue with the study of greedy-type bases in quasi-Banach spaces started in [3]. In this paper, we study partially-greedy bases focusing our attention in two main results: -Characterization of partially-greedy bases in quasi-Banach…

Functional Analysis · Mathematics 2020-04-03 Pablo M. Berná

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

We deal with the boundedness of the multilinear fractional integral operator $I_{\gamma,m}$ from a product of weighted Lebesgue spaces into adequate weighted Lipschitz spaces. Our results generalize some previous estimates not only for the…

Classical Analysis and ODEs · Mathematics 2022-03-09 Fabio Berra , Gladis Pradolini , Wilfredo Ramos

We consider the problem of approximating a given element $f$ from a Hilbert space $\mathcal{H}$ by means of greedy algorithms and the application of such procedures to the regression problem in statistical learning theory. We improve on the…

Statistics Theory · Mathematics 2009-09-29 Andrew R. Barron , Albert Cohen , Wolfgang Dahmen , Ronald A. DeVore

Garling sequence spaces admit a renorming with respect to which their standard unit vector basis is 1-greedy. We also discuss some additional properties of these Banach spaces related to uniform convexity and superreflexivity. In…

Functional Analysis · Mathematics 2017-05-12 Fernado Albiac , José L. Ansorena , Ben Wallis

This paper is a follow up to the previous author's paper on convex optimization. In that paper we began the process of adjusting greedy-type algorithms from nonlinear approximation for finding sparse solutions of convex optimization…

Machine Learning · Statistics 2012-06-05 V. N. Temlyakov

In this paper we develop a procedure to deal with a family of parameter-dependent ill-posed problems, for which the exact solution in general does not exist. The original problems are relaxed by considering corresponding approximate ones,…

Analysis of PDEs · Mathematics 2022-06-29 Martin Lazar , Enrique Zuazua

This article closes the cycle of characterizations of greedy-like bases in the isometric case initiated in [F. Albiac and P. Wojtaszczyk, Characterization of $1$-greedy bases, J. Approx. Theory 138 (2006)] with the characterization of…

Functional Analysis · Mathematics 2015-08-18 F. Albiac , J. L. Ansorena

The aim of this paper is to develop greedy algorithms which generate uniformly distributed sequences in the $d$-dimensional unit cube $[0,1]^d$. The figures of merit are three different variants of $L_2$ discrepancy. Theoretical results…

Number Theory · Mathematics 2022-10-19 Ralph Kritzinger

Kernel based methods provide a way to reconstruct potentially high-dimensional functions from meshfree samples, i.e., sampling points and corresponding target values. A crucial ingredient for this to be successful is the distribution of the…

Numerical Analysis · Mathematics 2021-05-19 Tizian Wenzel , Gabriele Santin , Bernard Haasdonk