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Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023 In this paper, we introduce Max Markov Chain (MMC), a novel model for sequential data with sparse correlations among the state variables. It may also be viewed as a special class of approximate models for High-order Markov Chains (HMCs). MMC is desirable for domains where the sparse correlations are long-term and vary in their temporal stretches ...
Yu Zhang, Mitchell Bucklew
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Rank-driven Markov processes [PDF]
, 2012 We study a class of Markovian systems of N elements taking values in [0,1] that evolve in discrete time t via randomized replacement rules based on the ranks of the elements.
Grinfeld, Michael +2 more
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Information geometry of Markov Kernels: a survey
Frontiers in Physics, 2023 Information geometry and Markov chains are two powerful tools used in modern fields such as finance, physics, computer science, and epidemiology. In this survey, we explore their intersection, focusing on the theoretical framework.
Geoffrey Wolfer, Shun Watanabe
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Unpredictability in Markov chains [PDF]
Carpathian Journal of Mathematics, 2021 We have formalized realizations of Markov chains as conveniently constructed sequences, and explained, why the random dynamics admits the unpredictability, the concept introduced in our papers previously. The method of the domain structured dynamics (dynamics on labels) has been applied.
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Correction : perfect simulation for a class of positive recurrent Markov chains [PDF]
, 2007 In [1] we introduced a class of positive recurrent Markov chains, named tame chains. A perfect simulation algorithm, based on the method of dominated CFTP, was then shown to exist in principle for such chains. The construction of a suitable dominating
Connor, Stephen B., Kendall, W. S.
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Small sets and Markov transition densities [PDF]
, 2002 The theory of general state-space Markov chains can be strongly related to the case of discrete state-space by use of the notion of small sets and associated minorization conditions. The general theory shows that small sets exist for all Markov chains on
Montana, Giovanni +2 more
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Optimal choice of word length when comparing two Markov sequences using a χ 2-statistic
BMC Genomics, 2017 Background Alignment-free sequence comparison using counts of word patterns (grams, k-tuples) has become an active research topic due to the large amount of sequence data from the new sequencing technologies.
Xin Bai +4 more
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Theoretical Computer Science, 2011 The article introduces constraint Markov chains as a new tool for specification. They are a generalization of interval Markov chains. Interval Markov chains extend Markov chains by labeling transitions with intervals, implying that each transition probability needs to be within the according interval.
Caillaud, Benoit +5 more
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Stochastic Processes with Expected Stopping Time [PDF]
Logical Methods in Computer ScienceMarkov chains are the de facto finite-state model for stochastic dynamical systems, and Markov decision processes (MDPs) extend Markov chains by incorporating non-deterministic behaviors.
Krishnendu Chatterjee, Laurent Doyen
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Multiplex Markov chains: Convection cycles and optimality
Physical Review Research, 2020 Multiplex networks are a common modeling framework for interconnected systems and multimodal data, yet we still lack fundamental insights for how multiplexity affects stochastic processes.
Dane Taylor
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