On Mixtures of Markov Chains
–Neural Information Processing Systems
We study the problem of reconstructing a mixture of Markov chains from the trajectories generated by random walks through the state space. Under mild nondegeneracy conditions, we show that we can uniquely reconstruct the underlying chains by only considering trajectories of length three, which represent triples of states. Our algorithm is spectral in nature, and is easy to implement.
Neural Information Processing Systems
Mar-12-2024, 14:14:43 GMT
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