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We analyze the convergence of generalized kernel-based interpolation methods. This is done under minimalistic assumptions on both the kernel and the target function. On these grounds, we further prove convergence of popular greedy data…

Numerical Analysis · Mathematics 2024-11-26 Kristof Albrecht , Armin Iske

We consider the problem of studying the performance of greedy algorithm on sensor selection problem for stable linear systems with Kalman Filter. Specifically, the objective is to find the system parameters that affects the performance of…

Data Structures and Algorithms · Computer Science 2017-07-10 Jingyuan Liu

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

Several recent deep neural networks experiments leverage the generalist-specialist paradigm for classification. However, no formal study compared the performance of different clustering algorithms for class assignment. In this paper we…

Machine Learning · Computer Science 2016-09-14 Sébastien Arnold

This paper is devoted to the theoretical study of the efficiency, namely, stability of some greedy algorithms. In the greedy approximation theory researchers are mostly interested in the following two important properties of an algorithm --…

Numerical Analysis · Mathematics 2025-12-25 V. N. Temlyakov

Kernel-based schemes are state-of-the-art techniques for learning by data. In this work we extend some ideas about kernel-based greedy algorithms to exponential-polynomial splines, whose main drawback consists in possible overfitting and…

Numerical Analysis · Mathematics 2022-10-31 Rosanna Campagna , Stefano De Marchi , Emma Perracchione , Gabriele Santin

A novel and detailed convergence analysis is presented for a greedy algorithm that was previously introduced for operator reconstruction problems in the field of quantum mechanics. This algorithm is based on an offline/online decomposition…

Optimization and Control · Mathematics 2020-11-02 S Buchwald , G Ciaramella , Julien Salomon

Submodular maximization has been widely studied over the past decades, mostly because of its numerous applications in real-world problems. It is well known that the standard greedy algorithm guarantees a worst-case approximation factor of…

Data Structures and Algorithms · Computer Science 2020-02-12 Alfredo Torrico , Mohit Singh , Sebastian Pokutta

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 greedy algorithm for approximating dominating sets is a simple method that is known to compute an $(\ln n+1)$-approximation of a minimum dominating set on any graph with $n$ vertices. We show that a small modification of the greedy…

Discrete Mathematics · Computer Science 2019-01-18 Sebastian Siebertz

We present convergence estimates of two types of greedy algorithms in terms of the metric entropy of underlying compact sets. In the first part, we measure the error of a standard greedy reduced basis method for parametric PDEs by the…

Numerical Analysis · Mathematics 2024-10-29 Yuwen Li , Jonathan Siegel

A flaw in the greedy approximation algorithm proposed by Zhang et al. for minimum connected set cover problem is corrected, and a stronger result on the approximation ratio of the modified greedy algorithm is established. The results are…

Data Structures and Algorithms · Computer Science 2015-03-19 Wei Ren , Qing Zhao

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

In dictionary selection, several atoms are selected from finite candidates that successfully approximate given data points in the sparse representation. We propose a novel efficient greedy algorithm for dictionary selection. Not only does…

Machine Learning · Computer Science 2018-09-10 Kaito Fujii , Tasuku Soma

Optimal experimental design (OED) concerns itself with identifying ideal methods of data collection, e.g.~via sensor placement. The \emph{greedy algorithm}, that is, placing one sensor at a time, in an iteratively optimal manner, stands as…

Optimization and Control · Mathematics 2025-10-15 Christian Aarset

We derive new results for the performance of a simple greedy algorithm for finding large independent sets and matchings in constant degree regular graphs. We show that for $r$-regular graphs with $n$ nodes and girth at least $g$, the…

Discrete Mathematics · Computer Science 2008-07-09 David Gamarnik , David Goldberg

We show that the decreasing rearrangement of the Fourier series with respect to the Jacobi polynomials for functions in $L_p$ does not converge unless $p=2$. As a by-product of our work on quasi-greedy bases in $L_{p}(\mu)$, we show that no…

Functional Analysis · Mathematics 2015-07-22 Fernando Albiac , José L. Ansorena , Óscar Ciaurri , Juan L. Varona

We study the problem of fairly allocating a set of indivisible goods among agents with additive valuations. The extent of fairness of an allocation is measured by its Nash social welfare, which is the geometric mean of the valuations of the…

Computer Science and Game Theory · Computer Science 2018-07-23 Siddharth Barman , Sanath Kumar Krishnamurthy , Rohit Vaish

We generalize several theorems of R\'enyi, Parry, Dar\'oczy and K\'atai by characterizing the greedy and quasi-greedy expansions in non-integer bases.

Number Theory · Mathematics 2007-10-17 Claudio Baiocchi , Vilmos Komornik

Is it possible to maximize a monotone submodular function faster than the widely used lazy greedy algorithm (also known as accelerated greedy), both in theory and practice? In this paper, we develop the first linear-time algorithm for…

Machine Learning · Computer Science 2014-12-01 Baharan Mirzasoleiman , Ashwinkumar Badanidiyuru , Amin Karbasi , Jan Vondrak , Andreas Krause