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generalized probabilistic descent.
It is learned via the minimum classification error (MCE) approach with generalized probabilistic descent (GPD) [16].
The relevance weights for each stream could be fixed a priori by an expert [13], or learned via Minimum Classification Error/Generalized Probabilistic Descent (MCE/GPD) [16].
Third, we generalize the maximum likelihood based Baum-Welch algorithm and the minimum classification error/gradient probabilistic descent (MCE/GPD) learning algorithms to include stream relevance weights.
This new parameter set w ˜ jm is trained by using the generalized probabilistic descent (GPD) algorithm [16] as w ˜ jm n + 1 = w ˜ jm n − ϵ ∇ l k w ˜ jm n, (13).
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