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Unlike the experts which can be bounded with *EM* and reduce to
logarithms of Gaussians, the gates can not be as easily differentiated
and set to 0. They are bounded by Jensen *and* the
bounding and the Gaussians of the gates do not reside nicely
within a logarithm. In fact, *additional* bounding operations are
sometimes necessary and thus, it is important to break down the
optimization of the gates. We shall separately consider the mixing
proportions (), the means ()
and the covariances
(
). This separation facilitates our derivation but the
trade-off is that each iteration involves 4 steps: 1) optimize the
experts, 2) optimize the gate mixing proportions, 3) optimize the gate
means and 4) optimize the gate covariances^{7.1}. This ECM-type [41]
approach may seem cumbersome and theoretically we would like to
maximize all simultaneously. However, the above separation yields a
surprisingly efficient implementation and in practice the numerical
computations converge efficiently.

*Tony Jebara*

*1999-09-15*