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 …

Parameterized complexity/multivariate complexity algorithmics is an exciting field of modern
algorithm design and analysis, with a broad range of theoretical and practical aspects that …

Inspired by a width invariant defined on permutations by Guillemot and Marx [SODA'14], we
introduce the notion of twin-width on graphs and on matrices. Proper minor-closed classes …

The goal of this textbook is twofold. First, the book serves as an introduction to the field of
parameterized algorithms and complexity accessible to graduate students and advanced …

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 …

We recently introduced the notion of twin-width, a novel graph invariant, and showed that
first-order model checking can be solved in time for-vertex graphs given with a witness that …

Consider the following two-player communication process to decide a language L: The first
player holds the entire input x but is polynomially bounded; the second player is …

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 …

The OR-SAT problem asks, given Boolean formulae Φ1,..., Φm each of size at most n,
whether at least one of the Φi's is satisfiable. We show that there is no reduction from OR …