2 research outputs found
Minimization on mixture family
Iterative minimization algorithms appear in various areas including machine
learning, neural network, and information theory. The em algorithm is one of
the famous one in the former area, and Arimoto-Blahut algorithm is a typical
one in the latter area. However, these two topics had been separately studied
for a long time. In this paper, we generalize an algorithm that was recently
proposed in the context of Arimoto-Blahut algorithm. Then, we show various
convergence theorems, one of which covers the case when each iterative step is
done approximately. Also, we apply this algorithm to the target problem in em
algorithm, and propose its improvement. In addition, we apply it to other
various problems in information theory