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Factorial Hidden Markov Models
(1996-02-09)
We present a framework for learning in hidden Markov models with distributed state representations. Within this framework, we derive a learning algorithm based on the Expectation--Maximization (EM) procedure for maximum ...
Gaussian processes for state space models and change point detection
(University of CambridgeDepartment of Engineering, 2012-02-07)
This thesis details several applications of Gaussian processes (GPs) for enhanced time series modeling.
We first cover different approaches for using Gaussian processes in time series problems.
These are extended to the ...