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

Given an undirected graph with edge weights and a subset R of its edges, the Rural
Postman Problem (RPP) is to find a closed walk of minimum total weight containing all …

Makespan minimization (on parallel identical or unrelated machines) is arguably the most
natural and studied scheduling problem. A common approach in practical algorithm design …

Problems related to finding induced subgraphs satisfying given properties form one of the
most studied areas within graph algorithms. However, for many applications, it is desirable …

The celebrated notion of important separators bounds the number of small $(S, T) $-
separators in a graph which are'farthest from $ S $'in a technical sense. In this paper, we …

We revisit the k-Secluded Tree problem. Given a vertex-weighted undirected graph G, its
objective is to find a maximum-weight induced subtree T whose open neighborhood has …

Dealing with NP-hard problems, kernelization is a fundamental notion for polynomial-time
data reduction with performance guarantees: in polynomial time, a problem instance is …

For many problems, the important instances from practice possess certain structure that one
should reflect in the design of specific algorithms. As data reduction is an important and …

Preprocessing and data reduction are basic algorithmic tools. In parameterized algorithmics,
such preprocessing is defined by (problem) kernelization, where an equivalent instance (the …

We consider the Π-free Deletion problem parameterized by the size of a vertex cover, for a
range of graph properties Π. Given an input graph G, this problem asks whether there is a …