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• W2519852785 abstract "Stochastic models for interacting processes feature a dimensionality that grows exponentially with the number of processes. This state space explosion severely impairs the use of standard methods for the numerical analysis of such Markov chains. In this work, we develop algorithms for the approximation of steady states of structured Markov chains that consider tensor train decompositions, combined with well-established techniques for this problem – aggregation/disaggregation techniques. Numerical experiments demonstrate that the newly proposed algorithms are efficient on the determination of the steady state of a representative set of models." @default.
• W2519852785 created "2016-09-23" @default.
• W2519852785 creator A5052100168 @default.
• W2519852785 date "2016-01-01" @default.
• W2519852785 modified "2023-10-01" @default.
• W2519852785 title "Finding Steady States of Communicating Markov Processes Combining Aggregation/Disaggregation with Tensor Techniques" @default.
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• W2519852785 doi "https://doi.org/10.1007/978-3-319-46433-6_4" @default.
• W2519852785 hasPublicationYear "2016" @default.
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