Approximate inference in additive factorial HMMs with application to energy disaggregation

This paper considers additive factorial hidden Markov models, an extension to HMMs where the state factors into multiple independent chains, and the output is an additive function of all the hidden states. Although such models are very powerful, accurate inference is unfortunately difficult: exact i...

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Bibliographic Details
Main Authors: Kolter, Jeremy Z. (Contributor), Jaakkola, Tommi S. (Contributor)
Other Authors: Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory (Contributor), Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Contributor)
Format: Article
Language:English
Published: Proceedings of Machine Learning Research, 2018-05-11T17:10:28Z.
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