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2014 | 23 |
Article title

Markov State Space Aggregation via the Information Bottleneck Method

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PL
Abstracts
PL
Consider the problem of approximating a Markov chain by another Markov chain with a smaller state space that is obtained by partitioning the original state space. An information-theoretic cost function is proposed that is based on the relative entropy rate between the original Markov chain and a Markov chain defined by the partition. The state space aggregation problem can be sub-optimally solved by using the information bottleneck method.
Publisher
Year
Volume
23
Physical description
Dates
published
2014
online
21 - 05 - 2015
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Publication order reference
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YADDA identifier
bwmeta1.element.ojs-issn-2083-8476-year-2014-volume-23-article-2202
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