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- W2984833460 abstract "This paper studies the convergence of the stochastic algorithm of the modified Robbins–Monro form for a Markov random field (MRF), in which some of the nodes are clamped to be observed variables while the others are hidden ones. Based on the theory of stochastic approximation, we propose proper assumptions to guarantee the Hölder regularity of both the update function and the solution of the Poisson equation. Under these assumptions, it is proved that the control parameter sequence is almost surely bounded and accordingly the algorithm converges to the stable point of the log-likelihood function with probability [Formula: see text]." @default.
- W2984833460 created "2019-11-22" @default.
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- W2984833460 date "2019-11-18" @default.
- W2984833460 modified "2023-10-16" @default.
- W2984833460 title "Convergence of Markovian stochastic approximation for Markov random fields with hidden variables" @default.
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- W2984833460 doi "https://doi.org/10.1142/s021949372050029x" @default.
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