Multi-thread search with deterministic annealing EM algorithm

被引：1

作者：

Takada, M ^{[1
]}

Nakano, R ^{[1
]}

机构：

[1] Nagoya Inst Technol, Showa Ku, Nagoya, Aichi 4668555, Japan

来源：

PROCEEDING OF THE 2002 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOLS 1-3 | 2002年

关键词：

D O I：

10.1109/IJCNN.2002.1005618

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The EM algorithm is an efficient algorithm to obtain the ML estimate for incomplete data, but has the local optimality problem. The 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.

引用

页码：1034 / 1038

页数：3

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