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In the list-decodable learning setup, an overwhelming majority (say a $1-\beta$-fraction) of the input data consists of outliers and the goal of an algorithm is to output a small list $\mathcal{L}$ of hypotheses such that one of them agrees…

Data Structures and Algorithms · Computer Science 2019-05-14 Prasad Raghavendra , Morris Yau

We study a variation of the classical Shortest Common Superstring (SCS) problem in which a shortest superstring of a finite set of strings $S$ is sought containing as a factor every string of $S$ or its reversal. We call this problem…

Data Structures and Algorithms · Computer Science 2015-12-08 Gabriele Fici , Tomasz Kociumaka , Jakub Radoszewski , Wojciech Rytter , Tomasz Waleń

We prove a deterministic analogue of Rudelson's sampling theorem for sums of positive semidefinite matrices. Let $A_1,\dots,A_m$ be positive semidefinite \(d\times d\) matrices, and let $\lambda_1,\dots,\lambda_m \ge 0$ satisfy \[…

Functional Analysis · Mathematics 2026-05-22 Grigory Ivanov

Given $D$ and $\gamma>0$, whenever $c>0$ is sufficiently small and $n$ sufficiently large, if $\mathcal{G}$ is a family of $D$-degenerate graphs of individual orders at most $n$, maximum degrees at most $\tfrac{cn}{\log n}$, and total…

Combinatorics · Mathematics 2022-04-19 Peter Allen , Julia Böttcher , Jan Hladký , Diana Piguet

Optimal selection of a subset of items from a given set is a hard problem that requires combinatorial optimization. In this paper, we propose a subset selection algorithm that is trainable with gradient-based methods yet achieves…

Machine Learning · Computer Science 2018-10-31 Thomas Powers , Rasool Fakoor , Siamak Shakeri , Abhinav Sethy , Amanjit Kainth , Abdel-rahman Mohamed , Ruhi Sarikaya

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

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

This paper focuses on the development of novel greedy techniques for distributed learning under sparsity constraints. Greedy techniques have widely been used in centralized systems due to their low computational requirements and at the same…

Information Theory · Computer Science 2015-06-23 Symeon Chouvardas , Gerasimos Mileounis , Nicholas Kalouptsidis , Sergios Theodoridis

For a nonempty finite set $A$ of positive integers, let $\gcd\left(A\right)$ denote the greatest common divisor of the elements of $A$. Let $f\left(n\right)$ and $\Phi\left(n\right)$ denote, respectively, the number of subsets $A$ of…

Number Theory · Mathematics 2013-06-21 Prapanpong Pongsriiam

A subset of vertices is called a dissociation set if it induces a subgraph with vertex degree at most one. Recently, Yuan et al. established the upper bound of the maximum number of dissociation sets among all connected graphs of order n…

Combinatorics · Mathematics 2025-10-20 Pingshan Li , Ke Yang , Wei Jin

The random greedy algorithm for finding a maximal independent set in a graph constructs a maximal independent set by inspecting the graph's vertices in a random order, adding the current vertex to the independent set if it is not adjacent…

Combinatorics · Mathematics 2023-09-28 Michael Krivelevich , Tamás Mészáros , Peleg Michaeli , Clara Shikhelman

Given a set (or multiset) S of n numbers and a target number t, the subset sum problem is to decide if there is a subset of S that sums up to t. There are several methods for solving this problem, including exhaustive search,…

Data Structures and Algorithms · Computer Science 2018-07-17 Zhengjun Cao , Lihua Liu

For the past 25 years, one of the most studied algorithms in the field of Nonlinear Approximation Theory has been the Thresholding Greedy Algorithm. In this paper, we propose new summability methods for this algorithm, generating two new…

Functional Analysis · Mathematics 2025-05-02 Miguel Berasategui , Pablo M. Berná , Stephen J. Dilworth , Denka Kutzarova

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

Let $r\ge 3$ be a fixed constant and let $ {\mathcal H}$ be an $r$-uniform, $D$-regular hypergraph on $N$ vertices. Assume further that $ D > N^\varepsilon $ for some $ \varepsilon>0 $. Consider the random greedy algorithm for forming an…

Combinatorics · Mathematics 2024-09-25 Patrick Bennett , Tom Bohman

In 2015, Guth proved that if $S$ is a collection of $n$ $g$-dimensional semi-algebraic sets in $\mathbb{R}^d$ and if $D\geq 1$ is an integer, then there is a $d$-variate polynomial $P$ of degree at most $D$ so that each connected component…

Computational Geometry · Computer Science 2026-01-13 Pankaj K. Agarwal , Boris Aronov , Esther Ezra , Joshua Zahl

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

We study the awake complexity of graph problems that belong to the class O-LOCAL, which includes a subset of problems solvable by sequential greedy algorithms, such as $(\Delta+1)$-coloring and maximal independent set. It is known from…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-11-26 Alkida Balliu , Pierre Fraigniaud , Dennis Olivetti , Mikaël Rabie

The random greedy algorithm for constructing a large partial Steiner-Triple-System is defined as follows. We begin with a complete graph on $n$ vertices and proceed to remove the edges of triangles one at a time, where each triangle removed…

Combinatorics · Mathematics 2010-04-15 Tom Bohman , Alan Frieze , Eyal Lubetzky

We describe the Greedy Sparse Subspace Clustering (GSSC) algorithm providing an efficient method for clustering data belonging to a few low-dimensional linear or affine subspaces from incomplete corrupted and noisy data. We provide…

Numerical Analysis · Mathematics 2013-04-17 Alexander Petukhov , Inna Kozlov