Efficient Learning for Time Series Models by Non-Negative Moment Matrix Factorization: Supplemental Materials
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چکیده
This document contains derivations for the method-of-moments algorithms used in the paper. The first section describes the general approach to deriving multiplicative update rules for the components of a non-negative matrix factorization (NMF). The next section discusses the convergence properties of NMF. Then we give the pseudocode of the sequence clustering algorithm for mixture of HMMs. And finally, the derivations for the mixture of HMMs, the switching HMM, and the factorial HMM are given. Some of the notation used here may differ slightly from that of the paper.
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