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Related papers: Greedy-like bases for sequences with gaps

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$\newcommand{\eps}{\varepsilon}$ In this paper, we consider two important problems defined on finite metric spaces, and provide efficient new algorithms and approximation schemes for these problems on inputs given as graph shortest path…

Computational Geometry · Computer Science 2021-02-23 David Eppstein , Sariel Har-Peled , Anastasios Sidiropoulos

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

Motivated by recent work on stochastic gradient descent methods, we develop two stochastic variants of greedy algorithms for possibly non-convex optimization problems with sparsity constraints. We prove linear convergence in expectation to…

Numerical Analysis · Mathematics 2014-07-02 Nam Nguyen , Deanna Needell , Tina Woolf

We continue the study initiated in [F. Albiac and P. Wojtaszczyk, Characterization of $1$-greedy bases, J. Approx. Theory 138 (2006), no. 1, 65-86] of properties related to greedy bases in the case when the constants involved are sharp,…

Functional Analysis · Mathematics 2023-04-13 Fernando Albiac , Jose L. Ansorena , Oscar Blasco , Hung Viet Chu , Timur Oikhberg

In this paper we introduce several extremal sequences of points on locally compact metric spaces and study their asymptotic properties. These sequences are defined through a greedy algorithm by minimizing a certain energy functional whose…

Mathematical Physics · Physics 2019-10-22 A. López García

It was previously known that the almost greedy (AG) property essentially remains the same when we enlarge greedy sums in the classical definition by a factor $\lambda \geqslant 1$. The present paper shows that if instead, we enlarge greedy…

Functional Analysis · Mathematics 2025-12-11 Hung Viet Chu

We study the greedy (exploitation-only) algorithm in bandit problems with a known reward structure. We allow arbitrary finite reward structures, while prior work focused on a few specific ones. We fully characterize when the greedy…

Machine Learning · Computer Science 2025-11-10 Aleksandrs Slivkins , Yunzong Xu , Shiliang Zuo

We investigate properties of the $m$-th error of approximation by polynomials with constant coefficients $\mathcal{D}_{m}(x)$ and with modulus-constant coefficients $\mathcal{D}_{m}^{\ast}(x)$ introduced by Bern\'a and Blasco (2016) to…

Functional Analysis · Mathematics 2019-03-06 Pablo M. Berná , Antonio Pérez

We discuss the upper and lower estimates for the rate of convergence of Pure and Orthogonal Greedy Algorithms for dictionary with bounded cumulative coherence.

Numerical Analysis · Mathematics 2009-11-10 Eugene Livshitz

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 a fundamental problem in Bayesian learning, where the goal is to select a set of data sources with minimum cost while achieving a certain learning performance based on the data streams provided by the selected data sources. First,…

Machine Learning · Computer Science 2021-05-04 Lintao Ye , Aritra Mitra , Shreyas Sundaram

Motivated by the change-making problem, we extend the notion of greediness to sets of positive integers not containing the element $1$, and from there to numerical semigroups. We provide an algorithm to determine if a given set (not…

Combinatorics · Mathematics 2024-12-17 Hebert Pérez-Rosés , José Miguel Serradilla-Merinero , Maria Bras-Amorós

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 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

The fact that finite direct sums of two or more mutually different spaces from the family $\{\ell_{p} : 1\le p<\infty\}\cup c_{0}$ fail to have greedy bases is stated in [Dilworth et al., Greedy bases for Besov spaces, Constr. Approx. 34…

Functional Analysis · Mathematics 2014-01-21 Fernando Albiac , José L. Ansorena

Tsirelson's space $\mathcal{T}$ made its appearance in Banach space theory in 1974 soon to become one of the most significant counterexamples in the theory. Its structure broke the ideal pattern that analysts had conceived for a generic…

Functional Analysis · Mathematics 2022-11-22 Fernando Albiac , José L. Ansorena

We show that a (semi-normalized) basis in a Banach space is quasi-greedy with quasi-greedy constant equal to 1 if and only if it is unconditional with suppression-unconditional constant equal to 1.

Functional Analysis · Mathematics 2015-04-20 Fernando Albiac , Jose L. Ansorena

In this paper we proof that there exists a function f(x) belongs to L^1[0,1] such that a greedy algorithm with regard to generalized Walsh system does not converge to f(x) in L^1[0,1] norm, i.e. the generalized Walsh system is not a…

Functional Analysis · Mathematics 2011-09-20 Sergo A. Episkoposian

Finding a minimum vertex cover in a network is a fundamental NP-complete graph problem. One way to deal with its computational hardness, is to trade the qualitative performance of an algorithm (allowing non-optimal outputs) for an improved…

Data Structures and Algorithms · Computer Science 2023-12-14 Thomas Bläsius , Tobias Friedrich , Maximilian Katzmann

This paper describes a simple greedy D-approximation algorithm for any covering problem whose objective function is submodular and non-decreasing, and whose feasible region can be expressed as the intersection of arbitrary (closed upwards)…

Data Structures and Algorithms · Computer Science 2015-06-02 Christos Koufogiannakis , Neal E. Young
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