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Learning a Hybrid Architecture for Sequence Regression and Annotation
When learning a hidden Markov model (HMM), sequen- tial observations can often be complemented by real-valued summary response variables generated from the path of hid- den states.
Non-stationary dynamic Bayesian networks
A principled mechanism for identifying conditional dependencies in time-series data is provided through structure learning of dynamic Bayesian networks (DBNs).
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