Kernelization : Theory of Parameterized Preprocessing / by F. V. Fomin and others. [Electronic Resource]
Material type: Computer filePublication details: Cambridge : Cambridge University Press, 2019Description: xiv, 516pISBN:- 9781107415157
- 005.72 F731K
Item type | Home library | Collection | Call number | Status | Notes | Date due | Barcode | Item holds |
---|---|---|---|---|---|---|---|---|
e-Book | S. R. Ranganathan Learning Hub Online | Textbook | 005.72 F731K (Browse shelf(Opens below)) | Available | Platform : Cambridge Core | EB0387 |
Browsing S. R. Ranganathan Learning Hub shelves, Shelving location: Online, Collection: Textbook Close shelf browser (Hides shelf browser)
005.133 M576E Effective Modern C++ : 42 Specific Ways to Improve Your Use of C++11 and C++14 | 005.262 H685A ARM Assembly Language : Fundamentals and Techniques | 005.7 H276D Data Ethics of Power : A Human Approach in the Big Data and AI Era | 005.72 F731K Kernelization : Theory of Parameterized Preprocessing | 005.73 N227C Compact Data Structures : A Practical Approach | 005.73 Ok1P Purely Functional Data Structures | 005.74 L118B Blockchain Foundations : For The Internet Of Value |
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.
There are no comments on this title.