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This paper presents a linear prioritized local algorithm that computes large independent sets on a random $d$-regular graph with small and fixed degree $d$. We studied experimentally the independence ratio obtained by the algorithm when $ d…

Data Structures and Algorithms · Computer Science 2021-08-18 Raffaele Marino , Scott Kirkpatrick

In this paper we present a greedy algorithm for solving the problem of the maximum partitioning of graphs with supply and demand (MPGSD). The goal of the method is to solve the MPGSD for large graphs in a reasonable time limit. This is done…

Artificial Intelligence · Computer Science 2015-07-31 Raka Jovanovic , Abdelkader Bousselham , Stefan Voss

We demonstrate that the greedy algorithm for reduction of divisors on metric graphs need not terminate by modeling the Euclidean algorithm in this context. We observe that any infinite reduction has a well defined limit allowing us to treat…

Combinatorics · Mathematics 2015-04-17 Spencer Backman

In this article we find exponential good approximation of the empirical neigbourhood distribution of symbolled random graphs conditioned to a given empirical symbol distribution and empirical pair distribution. Using this approximation we…

Probability · Mathematics 2014-06-13 K. Doku-Amponsah

Nearly three decades ago, Bar-Noy, Motwani and Naor showed that no online edge-coloring algorithm can edge color a graph optimally. Indeed, their work, titled "the greedy algorithm is optimal for on-line edge coloring", shows that the…

Data Structures and Algorithms · Computer Science 2021-05-17 Amin Saberi , David Wajc

We prove general nonlinear large deviation estimates similar to Chatterjee-Dembo's original bounds except that we do not require any second order smoothness. Our approach relies on convex analysis arguments and is valid for a broad class of…

Probability · Mathematics 2020-04-21 Fanny Augeri

Since Tinhofer proposed the MinGreedy algorithm for maximum cardinality matching in 1984, several experimental studies found the randomized algorithm to perform excellently for various classes of random graphs and benchmark instances. In…

Data Structures and Algorithms · Computer Science 2015-05-19 Bert Besser , Matthias Poloczek

We investigate theoretical guarantees for the false-negative rate (FNR) -- the fraction of true causal edges whose orientation is not recovered, under single-variable random interventions and an $\epsilon$-interventional faithfulness…

Machine Learning · Computer Science 2025-11-05 Mathieu Chevalley , Arash Mehrjou , Patrick Schwab

In this work, we propose a large-graph limit estimate of the matching coverage for several matching algorithms, on general graphs generated by the configuration model. For a wide class of {\em local} matching algorithms, namely, algorithms…

Probability · Mathematics 2025-09-22 Mohamed Habib Aliou Diallo Aoudi , Pascal Moyal , Vincent Robin

A significant generalization of the Erd\"os-R\'enyi random graph model is an `inhomogeneous' random graph where the edge probabilities vary according to vertex types. We identify the threshold value for this random graph with a finite…

Probability · Mathematics 2024-11-06 Hamin Jung

A $\delta$ once-reinforced random walk ($\delta$-ORRW) on connected graph is a self-interacting random walk which moves to its neighbors at each step according to the weights of the edges at that time, where the weights are $1$ on edges…

Probability · Mathematics 2026-03-30 Xiangyu Huang , Yong Liu , Kainan Xiang

We study using large deviation theory the fluctuations of time-integrated functionals or observables of the unbiased random walk evolving on Erd\"os-R\'enyi random graphs, and construct a modified, biased random walk that explains how these…

Statistical Mechanics · Physics 2019-03-06 Francesco Coghi , Jules Morand , Hugo Touchette

We prove tight upper bounds on the logarithmic derivative of the independence and matching polynomials of d-regular graphs. For independent sets, this theorem is a strengthening of the results of Kahn, Galvin and Tetali, and Zhao showing…

Combinatorics · Mathematics 2019-11-04 Ewan Davies , Matthew Jenssen , Will Perkins , Barnaby Roberts

The independent set problem is NP-hard and particularly difficult to solve in large sparse graphs. In this work, we develop an advanced evolutionary algorithm, which incorporates kernelization techniques to compute large independent sets in…

Data Structures and Algorithms · Computer Science 2015-09-03 Sebastian Lamm , Peter Sanders , Christian Schulz , Darren Strash , Renato F. Werneck

We consider the problem of searching for a node on a labelled random graph according to a greedy algorithm that selects a route to the desired node using metric information on the graph. Motivated by peer-to-peer networks two types of…

Statistical Mechanics · Physics 2013-05-29 David Lancaster

For statistics of rare events in systems obeying a large-deviation principle, the rate function is a key quantity. When numerically estimating the rate function one is always restricted to finite system sizes. Thus, if the interest is in…

Data Analysis, Statistics and Probability · Physics 2024-12-06 Peter Werner , Alexander K. Hartmann

We study the algorithmic task of finding a large independent set in a sparse Erd\H{o}s-R\'{e}nyi random graph with $n$ vertices and average degree $d$. The maximum independent set is known to have size $(2 \log d / d)n$ in the double limit…

Computational Complexity · Computer Science 2020-11-13 Alexander S. Wein

We study greedy-type algorithms such that at a greedy step we pick several dictionary elements contrary to a single dictionary element in standard greedy-type algorithms. We call such greedy algorithms {\it super greedy algorithms}. The…

Numerical Analysis · Mathematics 2010-10-27 Entao Liu , Vladimir N. Temlyakov

A $t$-spanner of a graph $G$ is a subgraph $H$ in which all distances are preserved up to a multiplicative $t$ factor. A classical result of Alth\"ofer et al. is that for every integer $k$ and every graph $G$, there is a $(2k-1)$-spanner of…

Data Structures and Algorithms · Computer Science 2019-03-19 Eden Chlamtáč , Michael Dinitz , Thomas Robinson

The study of graph-based submodular maximization problems was initiated in a seminal work of Kempe, Kleinberg, and Tardos (2003): An {\em influence} function of subsets of nodes is defined by the graph structure and the aim is to find…

Data Structures and Algorithms · Computer Science 2016-09-09 Edith Cohen