Learning mixture hierarchies

Advances in Neural Information Processing Systems

Volumn , Issue , 1999, Pages 606-612

  Vasconcelos, Nuno ^a   Lippman, Andrew ^a  

^a MIT MEDIA LAB   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER VISION; EARTHMOVING MACHINERY; MIXTURES;

BIAS AND VARIANCE; BOTTOM-UP FASHION; COMPUTATIONALLY EFFICIENT; DETERMINISTIC ANNEALING; ESTIMATION METHODS; EXPECTATION-MAXIMIZATION ALGORITHMS; HIERARCHICAL REPRESENTATION; MIXTURE COMPONENTS;

ALGORITHMS;

EID: 84898937980     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (6)

1. A. Dempster, N. Laird, and D. Rubin. Maximum-likelihood from Incomplete Data via the EM Algorithm. J. of the Royal Statistical Society, B-39, 1977.
2. H. Murase and S. Nayar. Visual Learning and Recognition of 3-D Objects from Appearence. International journal of Computer Vision, 14:5-24, 1995.
3. K. Rose, E. Gurewitz, and G. Fox. Vector Quantization by Determinisc Annealing. IEEE Trans, on Information Theory, Vol. 38, July 1992.
4. J. Simonoff. Smoothing Methods in Statistics. Springer-Verlag, 1996.
5. N. Vasconcelos and A. Lippman. Learning Mixture Hierarchies. Technical report, MIT Media Laboratory, 1998. Available from ftp://ftp.media.mit.edu/pub/ nuno/HierMix.ps.gz.
6. N. Vasconcelos and A. Lippman. Content-based Pre-Indexed Video. In Proc. Int. Conf. Image Processing, Santa Barbara, California, 1997.