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We present a general approximation framework for weighted integer covering problems. In a weighted integer covering problem, the goal is to determine a non-negative integer solution $x$ to system $\{ Ax \geq r \}$ minimizing a non-negative…

Discrete Mathematics · Computer Science 2017-04-28 Britta Peis , José Verschae , Andreas Wierz

The greedy algorithm adapted from Kruskal's algorithm is an efficient and folklore way to produce a $k$-spanner with girth at least $k+2$. The greedy algorithm has shown to be `existentially optimal', while it's not `universally optimal'…

Data Structures and Algorithms · Computer Science 2024-11-05 Yeyuan Chen

We generalize the matroid-theoretic approach to greedy algorithms to the setting of poset matroids, in the sense of Barnabei, Nicoletti and Pezzoli (1998) [BNP]. We illustrate our result by providing a generalization of Kruskal algorithm…

Combinatorics · Mathematics 2013-06-18 Luca Ferrari

A $t$-spanner of a graph is a subgraph that $t$-approximates pairwise distances. The greedy algorithm is one of the simplest and most well-studied algorithms for constructing a sparse spanner: it computes a $t$-spanner with $n^{1+O(1/t)}$…

Data Structures and Algorithms · Computer Science 2023-08-03 Bernhard Haeupler , D Ellis Hershkowitz , Zihan Tan

We consider a multi-agent model for fair division of mixed manna (i.e. items for which agents can have positive, zero or negative utilities), in which agents have additive utilities for bundles of items. For this model, we give several…

Artificial Intelligence · Computer Science 2019-12-18 Martin Aleksandrov , Toby Walsh

Kernel based regularized interpolation is a well known technique to approximate a continuous multivariate function using a set of scattered data points and the corresponding function evaluations, or data values. This method has some…

Numerical Analysis · Mathematics 2018-07-26 Gabriele Santin , Dominik Wittwar , Bernard Haasdonk

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 extend results known for the randomized Gauss-Seidel and the Gauss-Southwell methods for the case of a Hermitian and positive definite matrix to certain classes of non-Hermitian matrices. We obtain convergence results for a whole range…

Numerical Analysis · Mathematics 2023-01-02 Andreas Frommer , Daniel B. Szyld

Results on two different settings of asymptotic behavior of approximation characteristics of individual functions are presented. First, we discuss the following classical question for sparse approximation. Is it true that for any individual…

Numerical Analysis · Mathematics 2019-11-11 L. Burusheva , V. Temlyakov

We show the potential of greedy recovery strategies for the sparse approximation of multivariate functions from a small dataset of pointwise evaluations by considering an extension of the orthogonal matching pursuit to the setting of…

Numerical Analysis · Mathematics 2019-05-06 Ben Adcock , Simone Brugiapaglia

With a quite different way to determine the working rows, we propose a novel greedy Kaczmarz method for solving consistent linear systems. Convergence analysis of the new method is provided. Numerical experiments show that, for the same…

Numerical Analysis · Mathematics 2020-04-07 Hanyu Li , Yanjun Zhang

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

The paper gives a systematic study of the approximate versions of three greedy-type algorithms that are widely used in convex optimization. By approximate version we mean the one where some of evaluations are made with an error. Importance…

Machine Learning · Statistics 2014-12-11 Vladimir Temlyakov

For two countable ordinals $\alpha$ and $\beta$, a basis of a Banach space $X$ is said to be $(\alpha, \beta)$-quasi-greedy if it is 1) quasi-greedy, 2) $\mathcal{S}_\alpha$-unconditional but not $\mathcal{S}_{\alpha+1}$-unconditional, and…

Functional Analysis · Mathematics 2025-12-19 Kevin Beanland , Hung Viet Chu , Thomas Schlumprecht , András Zsák

An interesting result due to Dilworth et al. was that if we enlarge greedy sums by a constant factor $\lambda > 1$ in the condition defining the greedy property, then we obtain an equivalence of the almost greedy property, a strictly weaker…

Functional Analysis · Mathematics 2023-08-31 Hung Viet Chu

When developing robust preconditioners for multiphysics problems, fractional functions of the Laplace operator often arise and need to be inverted. Rational approximation in the uniform norm can be used to convert inverting those fractional…

Numerical Analysis · Mathematics 2024-07-23 James H. Adler , Xiaozhe Hu , Xue Wang , Zhongqin Xue

Set Cover is a classic NP-hard problem; as shown by Slav\'{i}k (1997) the greedy algorithm gives an approximation ratio of $\ln n - \ln \ln n + \Theta(1)$. A series of works by Lund \& Yannakakis (1994), Feige (1998), Moshkovitz (2015) have…

Data Structures and Algorithms · Computer Science 2017-02-17 David G. Harris

A class of fast greedy block Kaczmarz methods combined with general greedy strategy and average technique are proposed for solving large consistent linear systems. Theoretical analysis of the convergence of the proposed method is given in…

Numerical Analysis · Mathematics 2022-10-18 Aqin Xiao , Junfeng Yin , Ning Zheng

Greedy optimization methods such as Matching Pursuit (MP) and Frank-Wolfe (FW) algorithms regained popularity in recent years due to their simplicity, effectiveness and theoretical guarantees. MP and FW address optimization over the linear…

Machine Learning · Computer Science 2017-11-21 Francesco Locatello , Michael Tschannen , Gunnar Rätsch , Martin Jaggi

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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