Decision trees of low depth are beneficial for understanding and interpreting the data they
represent. Unfortunately, finding a decision tree of lowest complexity (depth or size) that …

The graph invariant twin-width was recently introduced by Bonnet, Kim, Thomassé, and
Watrigan. Problems expressible in first-order logic, which includes many prominent NP-hard …

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 present a new approach for learning the structure of a treewidth-bounded Bayesian
Network (BN). The key to our approach is applying an exact method (based on MaxSAT) …

Hypertree width is a prominent hypergraph invariant with many algorithmic applications in
constraint satisfaction and databases. We propose two novel characterisations for hypertree …

Graph coloring is the problem of coloring the vertices of a graph with as few colors as
possible, avoiding monochromatic edges. It is one of the most fundamental NP-hard …

In quantum computing and quantum information processing, graph states are a specific type
of quantum states which are commonly used in quantum networking and quantum error …

The recently introduced graph parameter tree-cut width plays a similar role with respect to
immersions as the graph parameter treewidth plays with respect to minors. In this paper, we …

We propose a new algorithmic method for computing the hypertree width of hypergraphs,
and we evaluate its performance empirically. At the core of our approach lies a novel …

Abstract This year's Parameterized Algorithms and Computational Experiments challenge
(PACE 2020) was devoted to the problem of computing the treedepth of a given graph …