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Greedy algorithm are in widespread use for sparse recovery because of its efficiency. But some evident flaws exists in most popular greedy algorithms, such as CoSaMP, which includes unreasonable demands on prior knowledge of target signal…

Information Theory · Computer Science 2009-08-18 Hao Zhang , Gang Li , Huadong Meng

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

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 approximation of a discrete probability distribution $\mathbf{t}$ by an $M$-type distribution $\mathbf{p}$ is considered. The approximation error is measured by the informational divergence $\mathbb{D}(\mathbf{t}\Vert\mathbf{p})$, which…

Information Theory · Computer Science 2016-07-28 Bernhard C. Geiger , Georg Böcherer

This paper presents a general asymptotic theory of sequential Bayesian estimation giving results for the strongest, almost sure convergence. We show that under certain smoothness conditions on the probability model, the greedy information…

Statistics Theory · Mathematics 2016-01-11 Janne V. Kujala

Asymptotics are given for the number of rational points in the domain of a morphism of weighted projective stacks whose images have bounded height and satisfy a (possibly infinite) set of local conditions. As a consequence we obtain results…

Number Theory · Mathematics 2026-03-25 Tristan Phillips

Greedy algorithms are widely used for problems in machine learning such as feature selection and set function optimization. Unfortunately, for large datasets, the running time of even greedy algorithms can be quite high. This is because for…

Machine Learning · Statistics 2017-03-09 Rajiv Khanna , Ethan Elenberg , Alexandros G. Dimakis , Sahand Negahban , Joydeep Ghosh

We analyse the size of an independent set in a random graph on $n$ vertices with specified vertex degrees, constructed via a simple greedy algorithm: order the vertices arbitrarily, and, for each vertex in turn, place it in the independent…

Probability · Mathematics 2015-10-20 Graham Brightwell , Svante Janson , Malwina Luczak

We extend some rate of convergence results of greedy quantization sequences already investigated in arXiv:1409.0732 [math.PR]. We show, for a more general class of distributions satisfying a certain control, that the quantization error of…

Probability · Mathematics 2020-04-01 Rancy El Nmeir , Harald Luschgy , Gilles Pagès

For Schauder bases, Dilworth et al. introduced and characterized the partially greedy property, which is strictly weaker than the (almost) greedy property. Later, Berasategui et al. defined and studied the strong partially greedy property…

Functional Analysis · Mathematics 2024-05-14 Hung Viet Chu

We introduce the problem of maximizing approximately $k$-submodular functions subject to size constraints. In this problem, one seeks to select $k$-disjoint subsets of a ground set with bounded total size or individual sizes, and maximum…

Data Structures and Algorithms · Computer Science 2021-01-19 Leqian Zheng , Hau Chan , Grigorios Loukides , Minming Li

In this paper, we develop constructive algorithms for generating quasi-uniform point sets and sequences over arbitrary two-dimensional triangular domains. Our proposed method, called the \emph{Voronoi-guided greedy packing} algorithm,…

Numerical Analysis · Mathematics 2026-04-07 Hengjun Xu , Takashi Goda

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

Submodular functions are a broad class of set functions, which naturally arise in diverse areas. Many algorithms have been suggested for the maximization of these functions. Unfortunately, once the function deviates from submodularity, the…

Discrete Mathematics · Computer Science 2017-07-17 Lin Chen , Moran Feldman , Amin Karbasi

We prove a number of \textit{a priori} estimates for weak solutions of elliptic equations or systems with vertically independent coefficients in the upper-half space. These estimates are designed towards applications to boundary value…

Classical Analysis and ODEs · Mathematics 2014-06-26 Pascal Auscher , Sebastian Stahlhut

Identifying breakpoints in piecewise regression is critical in enhancing the reliability and interpretability of data fitting. In this paper, we propose novel algorithms based on the greedy algorithm to accurately and efficiently identify…

Machine Learning · Statistics 2026-04-14 Taehyeong Kim , Hyungu Lee , Myungjin Kim , Hayoung Choi

The problem of column subset selection has recently attracted a large body of research, with feature selection serving as one obvious and important application. Among the techniques that have been applied to solve this problem, the greedy…

Data Structures and Algorithms · Computer Science 2021-11-16 Jason Altschuler , Aditya Bhaskara , Gang Fu , Vahab Mirrokni , Afshin Rostamizadeh , Morteza Zadimoghaddam

This paper proposes a greedy algorithm named as Big step greedy set cover algorithm to compute approximate minimum set cover. The Big step greedy algorithm, in each step selects p sets such that the union of selected p sets contains…

Data Structures and Algorithms · Computer Science 2015-06-16 Drona Pratap Chandu

Greedy embedding (or drawing) is a simple and efficient strategy to route messages in wireless sensor networks. For each source-destination pair of nodes s, t in a greedy embedding there is always a neighbor u of s that is closer to t…

Computational Geometry · Computer Science 2013-06-24 Martin Nöllenburg , Roman Prutkin

We consider meshless approximation for solutions of boundary value problems (BVPs) of elliptic Partial Differential Equations (PDEs) via symmetric kernel collocation. We discuss the importance of the choice of the collocation points, in…

Numerical Analysis · Mathematics 2025-04-29 Tizian Wenzel , Daniel Winkle , Gabriele Santin , Bernard Haasdonk