STATISTICAL PHYSICS, MIXTURES OF DISTRIBUTIONS, AND THE EM ALGORITHM

被引:64
作者
YUILLE, AL
STOLORZ, P
UTANS, J
机构
[1] CALTECH,JET PROP LAB,PASADENA,CA 91109
[2] INT COMP SCI INST,BERKELEY,CA 94704
[3] SANTA FE INST,SANTA FE,NM 87501
关键词
D O I
10.1162/neco.1994.6.2.334
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
We show that there are strong relationships between approaches to optmization and learning based on statistical physics or mixtures of experts. In particular, the EM algorithm can be interpreted as converging either to a local maximum of the mixtures model or to a saddle point solution to the statistical physics system. An advantage of the statistical physics approach is that it naturally gives rise to a heuristic continuation method, deterministic annealing, for finding good solutions.
引用
收藏
页码:334 / 340
页数:7
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