عنوان

Kernelization :

(Number (ISBN

1107415152

(Number (ISBN

9781107415157

Erroneous ISBN

1107057760

Erroneous ISBN

9781107057760

Title Proper

Kernelization :

General Material Designation

[Book]

Other Title Information

theory of parameterized preprocessing /

First Statement of Responsibility

Fedor V. Fomin, University of Bergen ; Daniel Lokshtanov, University of Bergen and University California Santa Barbara ; Saket Saurabh, Institute of Mathematical Sciences and University of Bergen ; Meirav Zehavi, Ben-Gurion University.

Place of Publication, Distribution, etc.

Cambridge :

Name of Publisher, Distributor, etc.

Cambridge University Press,

Date of Publication, Distribution, etc.

2019.

Date of Publication, Distribution, etc.

©2019

Specific Material Designation and Extent of Item

1 online resource (xiv, 515 pages)

Text of Note

Includes bibliographical references and indexes.

Text of Note

What is a kernel? -- Warm up -- Inductive priorities -- Crown decomposition -- Expansion lemma -- Linear programming -- Hypertrees -- Sunflower lemma -- Modules -- Matroids -- Representative families -- Greedy packing -- Euler's formula -- Introduction to treewidth -- Bidimensionality and protrusions -- Surgery on graphs -- Framework -- Instance selectors -- Polynomial parameter transformation -- Polynomial lower bounds -- Extending distillation -- Turing kernelization -- Lossy kernelization.

0

Text of Note

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.

Title

KERNELIZATION.

International Standard Book Number

1107057760

Data reduction.

Electronic data processing-- Data preparation.

Kernel functions.

Parameter estimation.

Data reduction.

Electronic data processing-- Data preparation.

Kernel functions.

Parameter estimation.

Number

Edition

Class number

Book number

Fomin, Fedor V.

Lokshtanov, Daniel,1984-

Saurabh, Saket

Zehavi, Meirav

Date of Transaction

20200822145738.0

Cataloguing Rules (Descriptive Conventions))

pn

Electronic name

[Book]

Y