TY  - BOOK
AU  - Fomin,Fedor V.
AU  - Lokshtanov,Daniel
AU  - Saurabh,Saket
AU  - Zehavi,Meirav
TI  - Kernelization: theory of parameterized preprocessing 
SN  - 9781107057760 (hardback)
AV  - QA76.9.D345 F66 2019
U1  - 005.72 F73K 23
PY  - 2019///
CY  - Cambridge
PB  - Cambridge University Press
KW  - Electronic data processing
KW  - Data preparation
KW  - Data reduction
KW  - Kernel functions
KW  - Parameter estimation
N1  - Includes bibliographical references and index
N2  - "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 developing area of preprocessing analysis known as kernelization. The authors provide an overview of basic methods and important results, with accessible explanations of the most recent advances in the area, such as meta-kernelization, representative sets, polynomial lower bounds, and lossy kernelization. The text is divided into four parts, which cover the different theoretical aspects of the area: upper bounds, meta-theorems, lower bounds, and beyond kernelization. The methods are demonstrated through extensive examples using a single data set. Written to be self-contained, the book only requires a basic background in algorithmics and will be of use to professionals, researchers and graduate students in theoretical computer science, optimization, combinatorics, and related fields"--
ER  -