Learning to be Bayesian without supervision

Advances in Neural Information Processing Systems

Volumn , Issue , 2007, Pages 1145-1152

  Raphan, Martin ^a   Simoncelli, Eero P ^a  

^a NEW YORK UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ADDITIVE GAUSSIAN NOISE; BAYESIAN ESTIMATORS; EMPIRICAL PERFORMANCE; ESTIMATION ERRORS; LEAST SQUARE; LIKELIHOOD FUNCTIONS; NON-PARAMETRIC; OBSERVATION MODEL; OBSERVED DATA; PARAMETRIC FAMILY; POSTERIOR DISTRIBUTIONS; PRIOR PROBABILITY;

GAUSSIAN NOISE (ELECTRONIC); PROBABILITY DENSITY FUNCTION;

ESTIMATION;

EID: 57349139183     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (13)

1. G. Casella, "An introduction to empirical Bayes data analysis," Amer. Statist., vol. 39, pp. 83-87, 1985.
2. J. S. Maritz and T. Lwin, Empirical Bayes Methods. Chapman & Hall, 2nd ed., 1989.
3. J. Berger, "Improving on inadmissible estimators in continuous exponential families with applications to simultaneous estimation of gamma scale parameters," The Annals of Staistics, vol. 8, pp. 545-571, 1980.
4. C. M. Stein, "Estimation of the mean of a multivariate normal distribution," Annals of Statistics, vol. 9, pp. 1135-1151, November 1981.
5. J. T. Hwang, "Improving upon standard estimators in discrete exponential families with applications to poisson and negative binomial cases," The Annals of Staistics, vol. 10, pp. 857-867, 1982.
6. K. Miyasawa, "An empirical bayes estimator of the mean of a normal population," Bull. Inst. Internat. Statist., vol. 38, pp. 181-188, 1956.
7. H. Robbins, "An empirical bayes approach to statistics," Proc. Third Berkley Symposium on Mathematcal Statistics, vol. 1, pp. 157-163, 1956.
8. M. Raphan and E. P. Simoncelli, "Empirical Bayes least squares estimation without an explicit prior." NYU Courant Inst. Tech. Report, 2007.
9. C. R. Loader, "Local likelihood density estimation," Annals of Statistics, vol. 24, no. 4, pp. 1602-1618, 1996.
10. D.W. Scott, Multivariate Density Estimation: Theory, Practice, and Visualization. JohnWiley, 1992.
11. A. Hyvarinen, "Estimation of non-normalized statistical models by score matching," Journal of Machine Learning Research, vol. 6, pp. 695-709, 2005.
12. F. Luisier, T. Blu, and M. Unser, "SURE-based wavelet thresholding integrating inter-scale dependencies," in Proc IEEE Int'l Conf on Image Proc, (Atlanta GA, USA), pp. 1457-1460, October 2006.
13. D. Donoho and I. Johnstone, "Adapting to unknown smoothness via wavelet shrinkage," J American Stat Assoc, vol. 90, December 1995.