Abstract
The EM algorithm is an efficient algorithm to obtain the ML estimate for incomplete data, but has the local optimality problem. The deterministic annealing expectation-maximization (DAEM) algorithm was once proposed to solve the problem, but is not guaranteed to obtain the global optimum since it employs a single token search. The paper investigates the possibility of the multiple-thread search with the DAEM algorithm for a Gaussian mixture. The experiments showed the minimal beam size to guarantee the global optimality is not so large for a Gaussian mixture, and the solution quality of the beam DAEM algorithm always exceeds the EM and DAEM algorithms.
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