The Probabilistic Method, 2nd Edition

by ;
Edition: 2nd
Format: Hardcover
Pub. Date: 2000-08-01
Publisher(s): Wiley-Interscience
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Summary

The leading reference on probabilistic methods in combinatorics-now expanded and updated When it was first published in 1991, The Probabilistic Method became instantly the standard reference on one of the most powerful and widely used tools in combinatorics. Still without competition nearly a decade later, this new edition brings you up to speed on recent developments, while adding useful exercises and over 30ew material. It continues to emphasize the basic elements of the methodology, discussing in a remarkably clear and informal style both algorithmic and classical methods as well as modern applications. The Probabilistic Method, Second Edition begins with basic techniques that use expectation and variance, as well as the more recent martingales and correlation inequalities, then explores areas where probabilistic techniques proved successful, including discrepancy and random graphs as well as cutting-edge topics in theoretical computer science. A series of proofs, or "probabilistic lenses," are interspersed throughout the book, offering added insight into the application of the probabilistic approach. New and revised coverage includes: * Several improved as well as new results * A continuous approach to discrete probabilistic problems * Talagrand's Inequality and other novel concentration results * A discussion of the connection between discrepancy and VC-dimension * Several combinatorial applications of the entropy function and its properties * A new section on the life and work of Paul Erdös-the developer of the probabilistic method

Author Biography

NOGA ALON, PhD, is a Baumritter Professor of Mathematics and Computer Science at Tel Aviv University. He is a member of the Israel National Academy of Sciences and received the Erd÷s Prize in 1989, the Feher Prize in 1991, and the Polya Prize in 2000. <p> . SPENCER, PhD, is Professor of Mathematics and Computer Science at the Courant Institute of New York University. He is the cofounder and coeditor of the journal Random Structures and Algorithms and is also a Sloane Foundation Fellow.

Table of Contents

Dedication v
Preface vii
Acknowledgments ix
Part 1 METHODS
The Basic Method
1(12)
The Probabilistic Method
1(2)
Graph Theory
3(3)
Combinatorics
6(2)
Combinatorial Number Theory
8(1)
Disjoint Pairs
9(1)
Exercises
10(3)
The Probabilistic Lens: The Erdos-Ko-Rado Theorem
12(1)
Linearity of Expectation
13(12)
Basics
13(1)
Splitting Graphs
14(2)
Two Quickies
16(1)
Balancing Vectors
17(1)
Unbalancing Lights
18(2)
Without Coin Flips
20(1)
Exercises
20(5)
The Probabilistic Lens: Bregman's Theorem
22(3)
Alterations
25(16)
Ramsey Numbers
25(2)
Independent Sets
27(1)
Combinatorial Geometry
28(1)
Packing
29(1)
Recoloring
30(3)
Continuous Time
33(4)
Exercises
37(4)
The Probabilistic Lens: High Girth and High Chromatic Number
38(3)
The Second Moment
41(22)
Basics
41(1)
Number Theory
42(3)
More Basics
45(2)
Random Graphs
47(3)
Clique Number
50(2)
Distinct Sums
52(1)
The Rodl Nibble
53(5)
Exercises
58(5)
The Probabilistic Lens: Hamiltonian Paths
60(3)
The Local Lemma
63(70)
The Lemma
63(2)
Property B and Multicolored Sets of Real Numbers
65(2)
Lower Bounds for Ramsey Numbers
67(1)
A Geometric Result
68(1)
The Linear Arboricity of Graphs
69(64)
The Probabilistic Lens: Local Coloring
130(3)
Pseudorandomness
133(22)
The Quadratic Residue Tournaments
134(3)
Eigenvalues and Expanders
137(5)
Quasi Random Graphs
142(6)
Exercises
148(7)
The Probabilistic Lens: Random Walks
150(5)
Part II TOPICS
Random Graphs
155(28)
Subgraphs
156(2)
Clique Number
158(2)
Chromatic Number
160(1)
Branching Processes
161(4)
The Giant Component
165(3)
Inside the Phase Transition
168(3)
Zero-One Laws
171(7)
Exercises
178(5)
The Probabilistic Lens: Counting Subgraphs
180(3)
Circuit Complexity
183(16)
Preliminaries
183(2)
Random Restrictions and Bounded-Depth Circuits
185(4)
More on Bounded-Depth Circuits
189(2)
Monotone Circuits
191(3)
Formulae
194(2)
Exercises
196(3)
The Probabilistic Lens: Maximal Antichains
197(2)
Discrepancy
199(16)
Basics
199(2)
Six Standard Deviations Suffice
201(3)
Linear and Hereditary Discrepancy
204(3)
Lower Bounds
207(2)
The Beck-Fiala Theorem
209(1)
Exercises
210(5)
The Probabilistic Lens: Unbalancing Lights
212(3)
Geometry
215(16)
The Greatest Angle among Points in Euclidean Spaces
216(1)
Empty Triangles Determined by Points in the Plane
217(1)
Geometrical Realizations of Sign Matrices
218(2)
&epsis;-Nets and VC-Dimensions of Range Spaces
220(5)
Dual Shatter Functions and Discrepancy
225(3)
Exercises
228(3)
The Probabilistic Lens: Efficient Packing
229(2)
Codes, Games and Entropy
231(18)
Codes
231(2)
Liar Game
233(3)
Tenure Game
236(1)
Balancing Vector Game
237(2)
Nonadaptive Algorithms
239(1)
Entropy
240(5)
Exercises
245(4)
The Probabilistic Lens: An Extremal Graph
247(2)
Derandomization
249(14)
The Method of Conditional Probabilities
249(4)
d-Wise Independent Random Variables in Small Sample Spaces
253(4)
Exercises
257(6)
The Probabilistic Lens: Crossing Numbers, Incidences, Sums and Products
259(4)
Appendix A: Bounding of Large Deviations 263(12)
A.1 Bounding of Large Deviations
263(8)
A.2 Exercises
271(4)
The Probabilistic Lens: Triangle-free Graphs Have Large Independence Numbers
272(3)
Appendix B: Paul Erdos 275(8)
B.1 Papers
275(2)
B.2 Conjectures
277(1)
B.3 On Erdos
278(1)
B.4 Uncle Paul
279(4)
References 283(12)
Subject Index 295(4)
Author Index 299

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