Sparsity : graphs, structures, and algorithms / Jaroslav Nesetril and Patrice Ossona de Mendez.
Material type: TextSeries: Algorithms and combinatorics ; 28.Publication details: Berlin : Springer-Verlag, 2012.Description: xxiii, 457 p. : ill. (some col.) ; 24 cmISBN:- 9783642278747 (hard cover : alk. paper)
- 511.6 23 N459
Item type | Current library | Call number | Status | Date due | Barcode | Item holds | |
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Books | ISI Library, Kolkata | 511.6 N459 (Browse shelf(Opens below)) | Available | 136985 |
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511.6 M663 Permanents | 511.6 M676 Transversal theory : an account of some aspects of combinatorial mathematics | 511.6 M678 Analytic combinatorics: a multidimensional approach/ | 511.6 N459 Sparsity : | 511.6 P226 Nonlinear assignment problems | 511.6 P393 Analytic combinatorics in several variables / | 511.6 P396 Computational discrete mathematics |
Includes bibliographical references and index.
1. Introduction --
2. A few problems --
3. Prolegomena --
4. Measuring sparsity --
5. Classes and their classification --
6. Bounded height trees and tree-depth --
7. Decomposition --
8. Independence --
9. First-order CSP, limits, and homomorphism dualities --
10. Preservation theorems --
11. Restricted homomorphism dualities --
12. Counting --
13. Back to classes --
14. Classes with bounded expansion --
15. Some applications --
16. Property testing, hyperfiniteness, and separators --
17. Core algorithms --
18. Algorithmic applications --
19. Further directions.
This is the first book devoted to the systematic study of sparse graphs and sparse finite structures. Although the notion of sparsity appears in various contexts and is a typical example of a hard to define notion, the authors devised an unifying classification of general classes of structures. This approach is very robust and it has many remarkable properties. For example the classification is expressible in many different ways involving most extremal combinatorial invariants. This study of sparse structures found applications in such diverse areas as algorithmic graph theory, complexity of algorithms, property testing, descriptive complexity and mathematical logic (homomorphism preservation, fixed parameter tractability and constraint satisfaction problems). It should be stressed that despite of its generality this approach leads to linear (and nearly linear) algorithms.
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