Infinite Factorial Unbounded-State Hidden Markov Model

IEEE Transactions on Pattern Analysis and Machine Intelligence, pp. 1816-1828, 2015.

Cited by: 16|Views9
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Abstract:

There are many scenarios in artificial intelligence, signal processing or medicine, in which a temporal sequence consists of several unknown overlapping independent causes, and we are interested in accurately recovering those canonical causes. Factorial hidden Markov models (FHMMs) present the versatility to provide a good fit to these sc...More

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