Deterministic Annealing Variant of the EM Algorithm

Part of Advances in Neural Information Processing Systems 7 (NIPS 1994)

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Naonori Ueda, Ryohei Nakano


We present a deterministic annealing variant of the EM algorithm for maximum likelihood parameter estimation problems. In our approach, the EM process is reformulated as the problem of min(cid:173) imizing the thermodynamic free energy by using the principle of maximum entropy and statistical mechanics analogy. Unlike simu(cid:173) lated annealing approaches, this minimization is deterministically performed. Moreover, the derived algorithm, unlike the conven(cid:173) tional EM algorithm, can obtain better estimates free of the initial parameter values.