Towards EM-style algorithms for a posteriori optimization of normal mixtures

IEEE International Symposium on Information Theory - Proceedings

Volumn , Issue , 1998, Pages 241-

  Ristad, E S ^a   Yianilos, P N ^b  

^a Mnemonic Technology Inc   (United States)

^b NEC LABORATORIES AMERICA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CLASS FUNCTIONS; CLASS PROBABILITIES; EXPECTATION MAXIMIZATION; INTRIGUING QUESTIONS; LABELED DATASET; NORMAL MIXTURES; OPTIMIZATION PROBLEMS; RE-WEIGHTING;

ALGORITHMS; INFORMATION THEORY; ITERATIVE METHODS; OPTIMIZATION;

MIXTURES;

EID: 84890368592     PISSN: 21578095     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ISIT.1998.708846     Document Type: Conference Paper

References (3)

1. L. E. BAUM AND J. E. EAGON, An inequality with application to statistical estimation for probabalistic functions of a Markov process and to models for ecology, Bull. AMS, 73 (1967), pp. 360-363.
2. A. P. DEMPSTER, N. M. LAIRD, AND D. B. RUBIN, Maximum-likelihood from incomplete data via the EM algorithm, J. Royal Statistical Society Ser. B (methodological), 39 (1977), pp. 1-38.
3. R. O. DUDA AND P. E. HART, Pattern Classification and Scene Analysis, John Wiley & Sons, Inc., 1973.