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Random walks and electric networks

by Peter G. Doyle, J. Laurie Snell , 2006
"... ..."
Abstract - Cited by 476 (11 self) - Add to MetaCart
Abstract not found

Reversible Markov chains and random walks on graphs

by David Aldous, James Allen Fill , 2002
"... ..."
Abstract - Cited by 541 (12 self) - Add to MetaCart
Abstract not found

Conditional random fields: Probabilistic models for segmenting and labeling sequence data

by John Lafferty , 2001
"... We present conditional random fields, a framework for building probabilistic models to segment and label sequence data. Conditional random fields offer several advantages over hidden Markov models and stochastic grammars for such tasks, including the ability to relax strong independence assumptions ..."
Abstract - Cited by 3485 (85 self) - Add to MetaCart
We present conditional random fields, a framework for building probabilistic models to segment and label sequence data. Conditional random fields offer several advantages over hidden Markov models and stochastic grammars for such tasks, including the ability to relax strong independence assumptions

Stock Market Prices Do Not Follow Random Walks: Evidence from a Simple Specification Test

by Andrew W. Lo, A. Craig MacKinlay - REVIEW OF FINANCIAL STUDIES , 1988
"... In this article we test the random walk hypothesis for weekly stock market returns by comparing variance estimators derived from data sampled at different frequencies. The random walk model is strongly rejected for the entire sample period (1962--1985) and for all subperiod for a variety of aggrega ..."
Abstract - Cited by 517 (17 self) - Add to MetaCart
In this article we test the random walk hypothesis for weekly stock market returns by comparing variance estimators derived from data sampled at different frequencies. The random walk model is strongly rejected for the entire sample period (1962--1985) and for all subperiod for a variety

Fast probabilistic algorithms for verification of polynomial identities

by J. T. Schwartz - J. ACM , 1980
"... ABSTRACT The starthng success of the Rabm-Strassen-Solovay pnmahty algorithm, together with the intriguing foundattonal posstbthty that axtoms of randomness may constttute a useful fundamental source of mathemaucal truth independent of the standard axmmaUc structure of mathemaUcs, suggests a wgorous ..."
Abstract - Cited by 520 (1 self) - Add to MetaCart
ABSTRACT The starthng success of the Rabm-Strassen-Solovay pnmahty algorithm, together with the intriguing foundattonal posstbthty that axtoms of randomness may constttute a useful fundamental source of mathemaucal truth independent of the standard axmmaUc structure of mathemaUcs, suggests a

Probabilistic Inference Using Markov Chain Monte Carlo Methods

by Radford M. Neal , 1993
"... Probabilistic inference is an attractive approach to uncertain reasoning and empirical learning in artificial intelligence. Computational difficulties arise, however, because probabilistic models with the necessary realism and flexibility lead to complex distributions over high-dimensional spaces. R ..."
Abstract - Cited by 736 (24 self) - Add to MetaCart
Probabilistic inference is an attractive approach to uncertain reasoning and empirical learning in artificial intelligence. Computational difficulties arise, however, because probabilistic models with the necessary realism and flexibility lead to complex distributions over high-dimensional spaces

Randomized Gossip Algorithms

by Stephen Boyd, Arpita Ghosh, Balaji Prabhakar, Devavrat Shah - IEEE TRANSACTIONS ON INFORMATION THEORY , 2006
"... Motivated by applications to sensor, peer-to-peer, and ad hoc networks, we study distributed algorithms, also known as gossip algorithms, for exchanging information and for computing in an arbitrarily connected network of nodes. The topology of such networks changes continuously as new nodes join a ..."
Abstract - Cited by 532 (5 self) - Add to MetaCart
method that solves the optimization problem over the network. The relation of averaging time to the second largest eigenvalue naturally relates it to the mixing time of a random walk with transition probabilities derived from the gossip algorithm. We use this connection to study the performance

Random Walks on Graphs: A Survey

by L. Lovász , 1993
"... ..."
Abstract - Cited by 407 (3 self) - Add to MetaCart
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Random walks for image segmentation

by Leo Grady - IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE , 2006
"... A novel method is proposed for performing multilabel, interactive image segmentation. Given a small number of pixels with user-defined (or predefined) labels, one can analytically and quickly determine the probability that a random walker starting at each unlabeled pixel will first reach one of the ..."
Abstract - Cited by 387 (21 self) - Add to MetaCart
A novel method is proposed for performing multilabel, interactive image segmentation. Given a small number of pixels with user-defined (or predefined) labels, one can analytically and quickly determine the probability that a random walker starting at each unlabeled pixel will first reach one

A Fast Quantum Mechanical Algorithm for Database Search

by Lov K. Grover - ANNUAL ACM SYMPOSIUM ON THEORY OF COMPUTING , 1996
"... Imagine a phone directory containing N names arranged in completely random order. In order to find someone's phone number with a probability of , any classical algorithm (whether deterministic or probabilistic) will need to look at a minimum of names. Quantum mechanical systems can be in a supe ..."
Abstract - Cited by 1135 (10 self) - Add to MetaCart
Imagine a phone directory containing N names arranged in completely random order. In order to find someone's phone number with a probability of , any classical algorithm (whether deterministic or probabilistic) will need to look at a minimum of names. Quantum mechanical systems can be in a
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