Higher-order Random Walk Methods for Data Analysis
<p> Markov random walk models are powerful analytical tools for multiple areas in machine learning, numerical optimizations and data mining tasks. The key assumption of a first-order Markov chain is memorylessness, which restricts the dependence of the transition distribution to the current st...
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| Language: | EN |
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Purdue University
2018
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| Online Access: | http://pqdtopen.proquest.com/#viewpdf?dispub=10790747 |