The Steiner tree problem (STP) in graphs is one of the most studied problems in
combinatorial optimization. Since its inception in 1970, numerous articles published in the …

Preprocessing, or data reduction, is a standard technique for simplifying and speeding up
computation. Written by a team of experts in the field, this book introduces a rapidly …

A geometric map** establishes a correspondence between two domains. Since no real
object has zero or negative volume, such a map** is required to be inversion-free …

Using machine learning to solve combinatorial optimization (CO) problems is challenging,
especially when the data is unlabeled. This work proposes an unsupervised learning …

Online algorithms with predictions is a popular and elegant framework for bypassing
pessimistic lower bounds in competitive analysis. In this model, online algorithms are …

Parameterization and approximation are two popular ways of co** with NP-hard
problems. More recently, the two have also been combined to derive many interesting …

We present a technique that allows for improving on some relative greedy procedures by
well-chosen (non-oblivious) local search algorithms. Relative greedy procedures are a …

In this paper we propose a new framework for analyzing the performance of preprocessing
algorithms. Our framework builds on the notion of kernelization from parameterized …

We consider the Connectivity Augmentation Problem (CAP), a classical problem in the area
of Survivable Network Design. It is about increasing the edge-connectivity of a graph by one …

While map** a quantum circuit to the physical layer one has to consider the numerous
constraints imposed by the underlying hardware architecture. Connectivity of the physical …