Accelerating Power Methods for Higher-order Markov Chains release_vdnjogqtk5hspizxs72wv75foq

by Gaohang Yu, Yi Zhou, Laishui Lv

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Higher-order Markov chains play a very important role in many fields, ranging from multilinear PageRank to financial modeling. In this paper, we propose two accelerated higher-order power methods for computing the limiting probability distribution of higher-order Markov chains, namely higher-order power method with momentum and higher-order quadratic extrapolation method. The convergence results are established, and numerical experiments are reported to show that the proposed algorithms are effective. In particular, the non-parametric higher-order quadratic extrapolation method is very competitive to some existing methods in the literature.
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Type  article
Stage   submitted
Date   2020-07-11
Version   v2
Language   en ?
arXiv  2003.00686v2
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