We investigate the parameterized complexity of Bayesian Network Structure Learning
(BNSL), a classical problem that has received significant attention in empirical but also …

We study the parameterized complexity of the Bounded-Degree Vertex Deletion problem
(BDD), where the aim is to find a maximum induced subgraph whose maximum degree is …

We revisit two well-studied problems, Bounded Degree Vertex Deletion and Defective
Coloring, where the input is a graph G and a target degree Δ, and we are asked either to edit …

Motivated by applications in sociology, economy and medicine, we study variants of the
Target Set Selection problem, first proposed by Kempe, Kleinberg and Tardos. In our …

Structural graph parameters, such as treewidth, pathwidth, and clique-width, are a central
topic of study in parameterized complexity. A main aim of research in this area is to …

Algorithms for computing or approximating optimal decompositions for decompositional
parameters such as treewidth or clique-width have so far traditionally been tailored to …

Treewidth is arguably the most important structural graph parameter leading to
algorithmically beneficial graph decompositions. Triggered by a strongly growing interest in …

Let P ℓ denote a path in a graph G=(V, E) with ℓ vertices. A vertex cover P ℓ set C in G is a
vertex subset such that every P ℓ in G has at least a vertex in C. The Vertex Cover P ℓ …

Combining the techniques of approximation algorithms and parameterized complexity has
long been considered a promising research area, but relatively few results are currently …

Abstract Fellows, Guo, Moser and Niedermeier [14] proved a generalization of Nemhauser
and Trotter's theorem, which applies to d-Bounded-Degree Vertex Deletion (to delete k …