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Probability on trees and networks

By: Contributor(s): Series: Cambridge series in statistical and probabilistic mathematics ; 42Publication details: New York, NY : Cambridge University Press, 2016.Description: xv, 699 page : illustrations (some color) ; 26 cmISBN:
  • 9781107160156
Subject(s): DDC classification:
  • 519.21 LYO-P
Online resources: Summary: Starting around the late 1950s, several research communities began relating the geometry of graphs to stochastic processes on these graphs. This book, twenty years in the making, ties together research in the field, encompassing work on percolation, isoperimetric inequalities, eigenvalues, transition probabilities, and random walks. Written by two leading researchers, the text emphasizes intuition, while giving complete proofs and more than 850 exercises. Many recent developments, in which the authors have played a leading role, are discussed, including percolation on trees and Cayley graphs, uniform spanning forests, the mass-transport technique, and connections on random walks on graphs to embedding in Hilbert space. This state-of-the-art account of probability on networks will be indispensable for graduate students and researchers alike.
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Item type Current library Call number Status Barcode
Book Book NISER LIBRARY 519.21 LYO-P (Browse shelf(Opens below)) Available 26348

Includes bibliographical references (pages (648-686) and index.

Starting around the late 1950s, several research communities began relating the geometry of graphs to stochastic processes on these graphs. This book, twenty years in the making, ties together research in the field, encompassing work on percolation, isoperimetric inequalities, eigenvalues, transition probabilities, and random walks. Written by two leading researchers, the text emphasizes intuition, while giving complete proofs and more than 850 exercises. Many recent developments, in which the authors have played a leading role, are discussed, including percolation on trees and Cayley graphs, uniform spanning forests, the mass-transport technique, and connections on random walks on graphs to embedding in Hilbert space. This state-of-the-art account of probability on networks will be indispensable for graduate students and researchers alike.

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