Questions tagged [markov-chains]

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Form of conditional observation probabilities in a POMDP

Consider a partially observable Markov decision process (POMDP), see here for a complete definition. My question is in relation to the conditional observation probabilities (denoted by $O(o|s',a)$ in ...
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Calssifying the Partitions of the problem Cycle Decomposition of Markov Chains

The book Cycle Representations of Markov Processes solves the problem of Mapping Stochastic Matrices induced from a Markov Chain into Partitions using a $\lambda$-preserving ($\lambda$ is a Lebesgue ...
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Cheeger constant of a graph versus conductance of a Markov chain

Given some graph $G$ with vertices $V$ and edges $E$, its Cheeger constant $h(G)$ is well defined as $$h(G) = \min_{S\subset V,0<|S|\leq|V|}\frac{|\partial S|}{|S|}.$$ Given some doubly-...
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Calibrating a Markov Chain with little data

I am trying to calibrate a Markov Chain. Usually you would have the amount that "moves" from one state to the other and then the resulting value, with data at any given time with the following ...
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What is the meaning of the output weights of a Conditional Random Field (CRF) model?

Problem When train my linear chain CRF with annotated observations, I feed it with a number of sequences containing observation values and a "ground-truth" label for each observation. I'm currently ...
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probability matrix from digraph adjacency matrix

All I have in hand is a adjacency matrix of a digraph with equal weight on every edge, is there a very simple way to convert this to a state change probability matrix?
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What's the relationship of max-flow-min-cut and Markov Random Fields?

I am trying to follow this paper [1]. There is a relationship between Markov Random Fields (MRF) to max-flow-min-cut. An MRF can be represented as an undirected graph, and you can find flow through it,...