Learning from dyadic data

Advances in Neural Information Processing Systems

Volumn , Issue , 1999, Pages 466-472

  Hofmann, Thomas ^a   Puzicha, Jan ^b   Jordan, Michael I ^a  

^a MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

^b UNIVERSITY OF BONN   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS;

DIFFERENT DOMAINS; EM ALGORITHMS; FINITE SET; HIERARCHICAL LATENT CLASS; MIXTURE MODEL; MODEL FITTING; PREFERENCE ANALYSIS;

COMPUTATIONAL LINGUISTICS;

EID: 84898959989     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (8)

1. Dempster, A.P., Laird, N.M., Rubin, D.B. (1977). M aximum likelihood from incomplete data via the EM algorithm. J. Royal Statist. Soc. B, 39, 1-38.
2. Hofmann, T., Puzicha, J. 1998. Statistical models for cooccurrence data. Tech. rept. Artifical Intelligence Laboratory Memo 1625, M.I.T.
3. Hofmann, T., Puzicha, J., Buhmann, J.M. (1998). Unsupervised texture segmentation in a deterministic annealing framework. IEEE Transactions on Pattern Analysis and Machine Intelligence, 20(8), 803-818.
4. Jordan, M.I., Jacobs, R.A. (1994). Hierarchical mixtures of experts and the EM algorithm. Neural Computation, 6(2), 181-214.
5. Meila, M., Jordan, M. I. 1998. Estimating Dependency Structure as a Hidden Variable. In: Advances in Neural Information Processing Systems 10.
6. Perdra, F.C.N., Tishby, N.Z., Lee, L. 1993. Distributional clustering of English words. Pages 183-190 of: Proceedings of the ACL.
7. Rose, K., Gurewitz, E., Fox, G. (1990). Statistical mechanics and phase transitions in clustering. Physical Review Letters, 65(8), 945-948.
8. Saul, L., Pereira, F. 1997. Aggregate and mixed-order Markov models for statistical language processing. In: Proceedings of the 2nd International Conference on Empirical Methods in Natural Language Processing.