Online Learning with Hidden Markov Models

  title={Online Learning with Hidden Markov Models},
  author={Gianluigi Mongillo and Sophie Den{\`e}ve},
  journal={Neural Computation},
We present an online version of the expectation-maximization (EM) algorithm for hidden Markov models (HMMs). The sufficient statistics required for parameters estimation is computed recursively with time, that is, in an online way instead of using the batch forward-backward procedure. This computational scheme is generalized to the case where the model parameters can change with time by introducing a discount factor into the recurrence relations. The resulting algorithm is equivalent to the… CONTINUE READING
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