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20202026
most citedEfficient Bayesian Network Structure Learning via Parameterized Local Search on Topological Orderings

1 citations · 1 across the 9 of their papers we have counts for

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6 papers · 1 filter

cs.DS2026

Recognizing Label-Connected Graphs

Ralf Klasing, George B. Mertzios, Hendrik Molter +2

In classical gossiping, each participant initially knows a distinct piece of information. Whenever two participants call each other, they exchange everything they know. We study Go…

cs.DS2026

Parameterized Local Search for Vertex Cover: When only the Search Radius is Crucial

Christian Komusiewicz, Nils Morawietz

A vertex set in a graph is a valid -swap for a vertex cover of if has size at most and , the symmetric differenc…

cs.DS2026

Towards Settling the Complexity of the Lettericity Problem

Mario Grobler, Nils Morawietz, Silas Cato Sacher

The lettericity of a graph is defined as the smallest size of an alphabet such that there is a word and a decoder $\mathcal{D} \subseteq Σ…

cs.CC2026

On the Hardness of Finding Temporally Connected Subgraphs of Any Size

Arnaud Casteigts, Christian Komusiewicz, Nils Morawietz

Temporal graphs are graphs whose edges are present only at certain points in time. Reachability in these graphs is defined via temporal paths, in which edges are traversed in incre…

cs.LO2026

The Descriptive Complexity of Relation Modification Problems

Florian Chudigiewitsch, Marlene Gründel, Christian Komusiewicz +2

A relation modification problem gets a logical structure and a natural number k as input and asks whether k modifications of the structure suffice to make it satisfy a predefined p…

cs.CC2026

A Parameterized-Complexity Framework for Finding Local Optima

Robert Ganian, Hung P. Hoang, Christian Komusiewicz +1

Local search is a fundamental optimization technique that is both widely used in practice and deeply studied in theory, yet its computational complexity remains poorly understood.…