Dependent Indian buffet processes

Journal of Machine Learning Research

Volumn 9, Issue , 2010, Pages 924-931

  Williamson, Sinead ^a   Orbanz, Peter ^a   Ghahramani, Zoubin ^a  

^a UNIVERSITY OF CAMBRIDGE   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

BAYESIAN INFERENCE; BINARY MATRIX; COVARIANCE FUNCTION; COVARIATES; DIRICHLET PROCESS; EXPLICIT MODELING; FEATURE MODELS; GAUSSIAN PROCESS MODELS; HIDDEN STRUCTURES; LATENT VARIABLE MODELS; MARKOV CHAIN MONTE CARLO; OBSERVATIONAL DATA; RANDOM MATRIX; REAL WORLD DATA;

ARTIFICIAL INTELLIGENCE; BAYESIAN NETWORKS; INFERENCE ENGINES;

VARIATIONAL TECHNIQUES;

EID: 84862293140     PISSN: 15324435     EISSN: 15337928     Source Type: Journal    
DOI: None     Document Type: Conference Paper

References (24)

1. Bartholomew, D. J. (1987). The foundations of factor analysis. Biometrika, 71(2), 221-232.
2. Damien, P. and Walker, S. G. (2001). Sampling truncated normal, beta, and gamma densities. Journal of Computational and Graphical Statistics, 10(2), 206-215.
3. Doshi-Velez, F., Miller, K. T., van Gael, J., and Teh, Y. W. (2009). Variational inference for the Indian buffet process. In Proceedings of the 12th International Conference on Artificial Intelligence and Statistics (AISTATS).
4. Duan, J. A., Guindani, M., and Gelfand, A. E. (2007). Generalized spatial Dirichlet process models. Biometrika, 94(4), 809-825.
5. Duane, S., Kennedy, A. D., Pendleton, B. J., and Roweth, D. (1987). Hybrid Monte Carlo. Physical Review Letters B, 195(2), 216-222.
6. Dunson, D. B. and Park, J.-H. (2008). Kernel stickbreaking processes. Biometrika, 95(2), 307-323.
7. Ferguson, T. S. (1973). A Bayesian analysis of some nonparametric problems. Annals of Statistics, 1(2).
8. Griffin, J. E. and Steel, M. F. J. (2006). Order-based dependent Dirichlet processes. Journal of the American Statistical Association, 101, 179-194.
9. Griffiths, T. L. and Ghahramani, Z. (2006). Infinite latent features models and the Indian buffet process. In Advances in Neural Information Processing Systems (NIPS) 2005 .
10. Hjort, N. L. (1990). Nonparametric Bayes estimators based on beta processes in models for life history data. Annals of Statistics, 18(3), 1259-1294.
11. Knowles, D. and Ghahramani, Z. (2007). Infinite sparse factor analysis and infinite independent component analysis. In 7th International Conference on Independent Component Analysis and Signal Separation (ICA).
12. MacEachern, S. N. (1999). Dependent nonparametric processes. In Proc. Bayesian Statist. Sci. Sect.
13. MacEachern, S. N. (2000). Dependent Dirichlet processes. Technical report, Ohio State University.
14. McLachlan, G. and Peel, D. (2000). Finite Mixture Models. John Wiley & Sons.
15. Miller, K. T., Griffiths, T. L., and Jordan, M. I. (2008). The phylogenetic Indian buffet process: A non-exchangeable nonparametric prior for latent features. In Uncertainty in Artificial Intelligence (UAI).
16. Miller, K. T., Griffiths, T. L., and Jordan, M. I. (2009). Nonparametric latent feature models for link prediction. In Advances in Neural Information Processing Systems (NIPS) 2009 .
17. Navarro, D. J. and Griffiths, T. L. (2008). Latent features in similarity judgment: A nonparametric Bayesian approach. Neural Computation, 20, 2597-2628.
18. Neal, R. M. (1997). Monte Carlo implementation of Gaussian process models for Bayesian regression and classification. Technical report, University of Toronto.
19. Neal, R. M. (2003). Slice sampling. Annals of Statistics, 31(3), 705-767.
20. Poliner, G. E. and Ellis, D. P. W. (2007). A discriminative model for polyphonic piano transcription. EURASIP J. Appl. Signal Process., 2007(1), 154-162.
21. Sudderth, E. B. and Jordan, M. I. (2009). Shared segmentation of natural scenes using dependent Pitman-Yor processes. In Advances in Neural Information Processing Systems (NIPS) 2008 .
22. Teh, Y. W., Jordan, M. I., Beal, M. J., and Blei, D. M. (2006). Hierarchical Dirichlet processes. Journal of the American Statistical Association, 101, 1566-1581.
23. Teh, Y. W., Görür, D., and Ghahramani, Z. (2007). Stick-breaking construction for the Indian buffet process. In Proceedings of the 11th Conference on Artificial Intelligence and Statistics.
24. Van Gael, J., Teh, Y. W., and Ghahramani, Z. (2009). The infinite factorial hidden Markov model. In Advances in Neural Information Processing Systems (NIPS) 2008 .