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Automatic 92 (2018) 123132Contents lists available at ScienceDirectAutomatica journal homepage: www.elsevier.com/locate/automaticaStochastic stability in Product and Maples Systems with Markovic Jumps Ioannis
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Define the graph structure where the stochastic stability analysis will be performed.
02
Assign initial values to the variables in the graph.
03
Calculate the messages being passed between variables using the max-product algorithm.
04
Update the values of the variables based on the messages received.
05
Repeat steps 3 and 4 until convergence criteria are met.

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Researchers in the fields of machine learning, probabilistic graphical models, and optimization.
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Stochastic stability in max-product refers to the property of a system whereby it remains stable under random perturbations or changes in its environment during optimization processes, particularly in graphical models.
Entities that utilize max-product algorithms in their computations, especially in fields like operations research or artificial intelligence, are typically required to file for stochastic stability.
Filling out stochastic stability in max-product involves providing specific data on system parameters, performance metrics, and the methods used to analyze stability under stochastic conditions.
The purpose of stochastic stability in max-product is to ensure that algorithms yield reliable and consistent results despite statistical variability or uncertainties that may arise.
Information reported on stochastic stability in max-product must include system configuration, conditions of analysis, performance results, and any assumptions made during the assessment.
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