Results 91 to 100 of about 11,505 (254)

Discovering Treewidth

open access: yes, 2005
Treewidth is a graph parameter with several interesting theoretical and practical applications. This survey reviews algorithmic results on determining the treewidth of a given graph, and finding a tree decomposition of small width. Both theoretical results, establishing the asymptotic computational complexity of the problem, as experimental work on ...
openaire   +3 more sources

Parameters Tied to Treewidth

open access: yesJournal of Graph Theory, 2016
AbstractTreewidth is a graph parameter of fundamental importance to algorithmic and structural graph theory. This article surveys several graph parameters tied to treewidth, including separation number, tangle number, well‐linked number, and Cartesian tree product number.
Daniel J. Harvey, David R. Wood
openaire   +4 more sources

Parameterized Approximation Schemes using Graph Widths

open access: yes, 2014
Combining the techniques of approximation algorithms and parameterized complexity has long been considered a promising research area, but relatively few results are currently known.
B. Courcelle   +14 more
core   +1 more source

Perfect Matching Under Precedence Constraints

open access: yesNetworks, Volume 87, Issue 2, Page 175-190, March 2026.
ABSTRACT In this article, we motivate and define variants of perfect matching under precedence constraints where a perfect matching is built incrementally and precedence constraints ensure that an edge may only be added to the matching if the edge's predecessor vertices have already been covered.
Christina Büsing, Corinna Mathwieser
wiley   +1 more source

Counting Complexity for Reasoning in Abstract Argumentation

open access: yes, 2018
In this paper, we consider counting and projected model counting of extensions in abstract argumentation for various semantics. When asking for projected counts we are interested in counting the number of extensions of a given argumentation framework ...
Fichte, Johannes K.   +2 more
core   +2 more sources

Size‐Ramsey Numbers of Structurally Sparse Graphs

open access: yesRandom Structures &Algorithms, Volume 68, Issue 2, March 2026.
ABSTRACT Size‐Ramsey numbers are a central notion in combinatorics and have been widely studied since their introduction by Erdős, Faudree, Rousseau, and Schelp in 1978. Research has mainly focused on the size‐Ramsey numbers of n$$ n $$‐vertex graphs with constant maximum degree Δ$$ \Delta $$.
Nemanja Draganić   +4 more
wiley   +1 more source

On the parameterized complexity of computing tree-partitions [PDF]

open access: yesDiscrete Mathematics & Theoretical Computer Science
We study the parameterized complexity of computing the tree-partition-width, a graph parameter equivalent to treewidth on graphs of bounded maximum degree.
Hans L. Bodlaender   +2 more
doaj   +1 more source

Securing the Unseen: A Comprehensive Exploration Review of AI‐Powered Models for Zero‐Day Attack Detection

open access: yesExpert Systems, Volume 43, Issue 3, March 2026.
ABSTRACT Zero‐day exploits remain challenging to detect because they often appear in unknown distributions of signatures and rules. The article entails a systematic review and cross‐sectional synthesis of four fundamental model families for identifying zero‐day intrusions, namely, convolutional neural networks (CNN), deep neural networks (DNN ...
Abdullah Al Siam   +3 more
wiley   +1 more source

Chordal Graphs, Even‐Hole‐Free Graphs and Sparse Obstructions to Bounded Treewidth

open access: yesJournal of Graph Theory, Volume 110, Issue 3, Page 351-365, November 2025.
ABSTRACT Even‐hole‐free graphs pose a central challenge in identifying hereditary classes of bounded treewidth. We investigate this matter by presenting and studying the following conjecture: for an integer t ≥ 4 and a graph H, every even‐hole‐free graph of large enough treewidth has an induced subgraph isomorphic to either K t or H, if (and only if) H
Sepehr Hajebi
wiley   +1 more source

Augmenting Naïve Bayes Classifiers with k-Tree Topology

open access: yesMathematics
The Bayesian network is a directed, acyclic graphical model that can offer a structured description for probabilistic dependencies among random variables.
Fereshteh R. Dastjerdi, Liming Cai
doaj   +1 more source

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