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 …

The survey is a comprehensive overview of the develo** area of parameterized
algorithms for graph modification problems. It describes state of the art in kernelization …

Kernelization is a formalization of efficient preprocessing, aimed mainly at combinatorially
hard problems. Empirically, preprocessing is highly successful in practice, eg, in state-of-the …

Nowhere dense graph classes, introduced by Nešetřil and Ossona de Mendez [2010, 2011],
form a large variety of classes of “sparse graphs” including the class of planar graphs …

We introduce the framework of cross-composition for proving kernelization lower bounds. A
classical problem L\and/or-cross-composes into a parameterized problem Q if it is possible …

Possibly the most famous algorithmic meta-theorem is Courcelle's theorem, which states that
all MSO-expressible graph properties are decidable in linear time for graphs of bounded …

Let F be a finite set of graphs. In the F-DELETION problem, we are given an n-vertex graph
G and an integer k as input, and asked whether at most k vertices can be deleted from G …

Bidimensionality theory appears to be a powerful framework in the development of meta-
algorithmic techniques. It was introduced by Demaine et al.[J. ACM 2005] as a tool to obtain …

The aim of this article is to motivate and describe the parameter ecology program, which
studies how different parameters contribute to the difficulty of classical problems. We call for …

The existence of a polynomial kernel for Odd Cycle Transversal was a notorious open
problem in parameterized complexity. Recently, this was settled by the present authors …