Analyzing the errors of unsupervised learning

ACL-08: HLT - 46th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Conference

Volumn , Issue , 2008, Pages 879-887

  Liang, Percy ^a   Klein, Dan ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DEPENDENCY MODEL; INDUCTION SYSTEM; LOCAL OPTIMA; MEASURING DISTANCES; META MODEL; ROBUST METHODS; THREE MODELS; TRAINING EXAMPLE; TWO PARAMETER;

COMPUTATIONAL LINGUISTICS;

ERRORS;

EID: 84859910906     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (20)

1. P.W. Adriaans. 1999. Learning shallow context-free languages under simple distributions. Technical report, Stanford University.
2. G. Carroll and E. Charniak. 1992. Two experiments on learning probabilistic dependency grammars from corpora. In Workshop Notes for Statistically-Based NLP Techniques, pages 1-13.
3. A. Clark and F. Thollard. 2005. PAC-learnability of probabilistic deterministic finite state automata. JMLR, 5:473-497.
4. A. Clark. 2001. Unsupervised induction of stochastic context free grammars with distributional clustering. In CoNLL.
5. S. Dasgupta and L. Schulman. 2007. A probabilistic analysis of EM for mixtures of separated, spherical Gaussians. JMLR, 8.
6. S. Dasgupta. 1999. Learning mixtures of Gaussians. In FOCS.
7. J. Feldman, R. O'Donnell, and R. A. Servedio. 2005. Learning mixtures of product distributions over discrete domains. In FOCS, pages 501-510.
8. S. Goldwater and T. Griffiths. 2007. A fully Bayesian approach to unsupervised part-of-speech tagging. In ACL.
9. T. Grenager, D. Klein, and C. D. Manning. 2005. Unsupervised learning of field segmentation models for information extraction. In ACL.
10. A. Haghighi and D. Klein. 2006. Prototype-based grammar induction. In ACL.
11. M. Johnson. 2007. Why doesn't EM find good HMM POS-taggers? In EMNLP/CoNLL.
12. D. Klein and C. D. Manning. 2004. Corpus-based induction of syntactic structure: Models of dependency and constituency. In ACL.
13. H. W. Kuhn. 1955. The Hungarian method for the assignment problem. Naval Research Logistic Quarterly, 2:83-97.
14. K. Kurihara and T. Sato. 2006. Variational Bayesian grammar induction for natural language. In International Colloquium on Grammatical Inference.
15. B. Merialdo. 1994. Tagging English text with a probabilistic model. Computational Linguistics, 20:155- 171.
16. F. Pereira and Y. Shabes. 1992. Inside-outside reestimation from partially bracketed corpora. In ACL.
17. D. Ron, Y. Singer, and N. Tishby. 1998. On the learnability and usage of acyclic probabilistic finite automata. Journal of Computer and System Sciences, 56:133- 152.
18. N. Smith and J. Eisner. 2005. Contrastive estimation: Training log-linear models on unlabeled data. In ACL.
19. N. Smith and J. Eisner. 2006. Annealing structural bias in multilingual weighted grammar induction. In ACL.
20. N. Srebro, G. Shakhnarovich, and S. Roweis. 2006. An investigation of computational and informational limits in Gaussian mixture clustering. In ICML, pages 865-872.