Emergent Mind
A Concise Information-Theoretic Derivation of the Baum-Welch algorithm
(1406.7002)
Published Jun 24, 2014
in
cs.IT
,
cs.LG
,
and
math.IT
Abstract
We derive the Baum-Welch algorithm for hidden Markov models (HMMs) through an information-theoretical approach using cross-entropy instead of the Lagrange multiplier approach which is universal in machine learning literature. The proposed approach provides a more concise derivation of the Baum-Welch method and naturally generalizes to multiple observations.
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