Name: Kernelization: Theory of Parameterized Preprocessing (en Inglés)
Price: 102.54 USD
Availability: InStock
Author: Fedor V. Fomin; Daniel Lokshtanov; Saket Saurabh; Meirav Zehavi
ISBN: 9781107057760

portada Kernelization: Theory of Parameterized Preprocessing (en Inglés)

Kernelization: Theory of Parameterized Preprocessing (en Inglés)

Formato

Libro Físico

Editorial

Cambridge University Press

Autor

Fedor V. Fomin; Daniel Lokshtanov; Saket Saurabh; Meirav Zehavi

Año

2019

Idioma

Inglés

N° páginas

528

Encuadernación

Tapa Dura

ISBN13

9781107057760

N° edición

Categorías

Ciencia y análisis de datos: generalidades
Análisis y captura de datos

Kernelization: Theory of Parameterized Preprocessing (en Inglés)

Fedor V. Fomin; Daniel Lokshtanov; Saket Saurabh; Meirav Zehavi (Autor) · Cambridge University Press · Tapa Dura

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Reseña del libro "Kernelization: Theory of Parameterized Preprocessing (en Inglés)"

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.