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Related papers: Greedy Set Cover Estimations

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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

We study the approximability of the maximum size independent set (MIS) problem in bounded degree graphs. This is one of the most classic and widely studied NP-hard optimization problems. We focus on the well known minimum degree greedy…

Data Structures and Algorithms · Computer Science 2020-02-03 Piotr Krysta , Mathieu Mari , Nan Zhi

We study the problem of selecting a subset of vectors from a large set, to obtain the best signal representation over a family of functions. Although greedy methods have been widely used for tackling this problem and many of those have been…

Signal Processing · Electrical Eng. & Systems 2023-05-16 Ehsan Tohidi , Mario Coutino , David Gesbert

This article develops a new theoretical basis for decomposing signals that are formed by the linear superposition of a finite number of modes. Each mode depends nonlinearly upon several parameters; we seek both these parameters and the…

Metric Geometry · Mathematics 2021-06-09 Michael Robinson

The priority model was introduced to capture "greedy-like" algorithms. Motivated by the success of advice complexity in the area of online algorithms, the fixed priority model was extended to include advice, and a reduction-based framework…

Data Structures and Algorithms · Computer Science 2022-01-27 Joan Boyar , Kim S. Larsen , Denis Pankratov

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

In this work, we study the multi-agent decision problem where agents try to coordinate to optimize a given system-level objective. While solving for the global optimal is intractable in many cases, the greedy algorithm is a well-studied and…

Multiagent Systems · Computer Science 2022-12-01 Rohit Konda , David Grimsman , Jason Marden

The classical problem of maximizing a submodular function under a matroid constraint is considered. Defining a new measure for the increments made by the greedy algorithm at each step, called the discriminant, improved approximation ratio…

Data Structures and Algorithms · Computer Science 2018-10-31 Nived Rajaraman , Rahul Vaze

In this note we study the greedy algorithm for combinatorial auctions with submodular bidders. It is well known that this algorithm provides an approximation ratio of $2$ for every order of the items. We show that if the valuations are…

Computer Science and Game Theory · Computer Science 2015-02-10 Shahar Dobzinski , Ami Mor

In the design of greedy algorithms for the maximum cardinality matching problem the utilization of degree information when selecting the next edge is a well established and successful approach. We define the class of "degree sensitive"…

Data Structures and Algorithms · Computer Science 2016-12-21 Bert Besser , Bastian Werth

We investigate at decision trees that incorporate both traditional queries based on one attribute and queries based on hypotheses about the values of all attributes. Such decision trees are similar to ones studied in exact learning, where…

Computational Complexity · Computer Science 2022-03-18 Mohammad Azad , Igor Chikalov , Shahid Hussain , Mikhail Moshkov , Beata Zielosko

I provide a novel approach to characterizing the set of interim realizable allocations, in the spirit of Matthews (1984) and Border (1991). The approach allows me to identify precisely why exact characterizations are difficult to obtain in…

Theoretical Economics · Economics 2022-10-11 Quitzé Valenzuela-Stookey

We study the approximability of instances of the minimum entropy set cover problem, parameterized by the average frequency of a random element in the covering sets. We analyze an algorithm combining a greedy approach with another one biased…

Data Structures and Algorithms · Computer Science 2012-08-01 Cosmin Bonchis , Gabriel Istrate

We consider a class of multi-agent optimal coverage problems in which the goal is to determine the optimal placement of a group of agents in a given mission space so that they maximize a coverage objective that represents a blend of…

Systems and Control · Electrical Eng. & Systems 2024-03-26 Shirantha Welikala , Christos G. Cassandras

The purpose of this article is to examine the greedy adaptive measurement policy in the context of a linear Guassian measurement model with an optimization criterion based on information gain. In the special case of sequential scalar…

Information Theory · Computer Science 2012-08-20 Entao Liu , Edwin K. P. Chong , Louis L. Scharf

We introduce a measure of {\em greedy connectivity} for geographical networks (graphs embedded in space) and where the search for connecting paths relies only on local information, such as a node's location and that of its neighbors.…

Statistical Mechanics · Physics 2015-05-18 Jie Sun , Daniel ben-Avraham

We develop greedy algorithms to approximate the optimal solution to the multi-fidelity sensor selection problem, which is a cost constrained optimization problem prescribing the placement and number of cheap (low signal-to-noise) and…

Signal Processing · Electrical Eng. & Systems 2020-05-08 Emily Clark , Steven L. Brunton , J. Nathan Kutz

This paper focuses on greedy expansions, one possible representation of numbers, and on arithmetical operations with them. Performing addition or multiplication some additional digits can appear. We study bounds on the number of such digits…

Number Theory · Mathematics 2022-12-16 Magdaléna Tinková

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

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
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