Random walk

Results: 630



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31ELSEVIER  Stochastic Processes and their Applications184 stochastic processes

ELSEVIER Stochastic Processes and their Applications184 stochastic processes

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Source URL: www.math.csi.cuny.edu

Language: English - Date: 2009-05-03 17:57:30
32Risks For the Long Run: Estimation and Inference∗ Ravi Bansal† Dana Kiku‡ Amir Yaron§ First Draft: June 2006

Risks For the Long Run: Estimation and Inference∗ Ravi Bansal† Dana Kiku‡ Amir Yaron§ First Draft: June 2006

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Source URL: faculty.fuqua.duke.edu

Language: English - Date: 2007-09-27 10:50:57
33Inference, Models and Simulation for Complex Systems Lecture 6 Prof. Aaron Clauset 1

Inference, Models and Simulation for Complex Systems Lecture 6 Prof. Aaron Clauset 1

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Source URL: tuvalu.santafe.edu

Language: English - Date: 2011-09-16 15:35:30
34Spectral Graph Theory and Applications  WSLecture 5: Random Walks and Markov Chain Lecturer: Thomas Sauerwald & He Sun

Spectral Graph Theory and Applications WSLecture 5: Random Walks and Markov Chain Lecturer: Thomas Sauerwald & He Sun

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Source URL: resources.mpi-inf.mpg.de

Language: English - Date: 2011-12-08 09:45:08
35Detecting malicious behavior in network and endpoint logs is an extremely challenging task: large and complex data sets, highly dynamic innocuous behavior, and intelligent adversaries contribute to the difficulty. Even a

Detecting malicious behavior in network and endpoint logs is an extremely challenging task: large and complex data sets, highly dynamic innocuous behavior, and intelligent adversaries contribute to the difficulty. Even a

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Source URL: mmds-data.org

Language: English - Date: 2016-06-23 15:50:48
36Proceedings of the 9th Conference on Interdisciplinary Musicology – CIM14. Berlin, GermanyM ISTIFY: DYNAMICALLY R ECREATING X ENAKIS ’ Mists Thor Kell1 1

Proceedings of the 9th Conference on Interdisciplinary Musicology – CIM14. Berlin, GermanyM ISTIFY: DYNAMICALLY R ECREATING X ENAKIS ’ Mists Thor Kell1 1

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Source URL: tide-pool.ca

Language: English - Date: 2014-12-06 10:29:43
37A NNALES DE L’I. H. P., SECTION B  E NDRE C SÁKI PÁL R ÉVÉSZ JAY ROSEN Functional laws of the iterated logarithm for local

A NNALES DE L’I. H. P., SECTION B E NDRE C SÁKI PÁL R ÉVÉSZ JAY ROSEN Functional laws of the iterated logarithm for local

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Source URL: www.math.csi.cuny.edu

Language: English - Date: 2009-05-03 17:57:56
38Mixing time on random walks Min Chen  Univ.of York research.btexact.com 2004 Nov 19 13:30

Mixing time on random walks Min Chen Univ.of York research.btexact.com 2004 Nov 19 13:30

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Source URL: www.monmeetings.org

Language: English - Date: 2015-09-04 10:25:00
39Detecting malicious behavior in network and endpoint logs is an extremely challenging task: large and complex data sets, highly dynamic innocuous behavior, and intelligent adversaries contribute to the difficulty. Even a

Detecting malicious behavior in network and endpoint logs is an extremely challenging task: large and complex data sets, highly dynamic innocuous behavior, and intelligent adversaries contribute to the difficulty. Even a

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Source URL: mmds-data.org

Language: English - Date: 2016-06-23 15:50:48
40

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Source URL: www.eurandom.tue.nl

Language: English - Date: 2016-07-13 03:43:30