Variational bridge regression

Journal of Machine Learning Research

Volumn 5, Issue , 2009, Pages 17-24

  Armagan, Artin ^a  

^a Duke University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

APPROXIMATE INFERENCE; FREQUENTIST; HIERARCHICAL MODELING; MAXIMUM A POSTERIORI; MIXING DISTRIBUTIONS; MODEL SELECTION; NORMAL MIXTURES; REGRESSION COEFFICIENT; SPECIFIC VALUES; STATE-OF-THE-ART PROCEDURES; SUBSET SELECTION; TUNING PARAMETER; VARIATIONAL METHODS;

ARTIFICIAL INTELLIGENCE; ESTIMATION;

REGRESSION ANALYSIS;

EID: 79956218795     PISSN: 15324435     EISSN: 15337928     Source Type: Journal    
DOI: None     Document Type: Conference Paper

References (15)

1. Albert, J. H. and Chib, S. "Bayesian Analysis of Binary and Polychotomous Response Data." Journal of the American Statistical Association, 88 (1993).
2. Andrews, D. F. and Mallows, C. L. "Scale Mixtures of Normal Distributions." Journal of the Royal Statistical Society. Series B (Methodological), 36(1):99-102 (1974).
3. Bishop, C. M. Pattern Recognition and Machine Learning. Springer (2006).
4. Bishop, C. M. and Tipping, M. E. "Variational Relevance Vector Machines." In UAI'00: Proceedings of the 16th Conference on Uncertainty in Artificial Intelligence, 46-53. San Francisco, CA, USA: Morgan Kaufmann Publishers Inc. (2000).
5. Breiman, L. "Better Subset Regression Using the Nonnegative Garrote." Technometrics, 37(4):373-384 (1995).
6. Figueiredo, M. A. T. "Adaptive sparseness for supervised learning." IEEE Transactions on Pattern Analysis and Machine Intelligence, 25:1150-1159 (2003).
7. Frank, I. E. and Friedman, J. H. "A Statistical View of Some Chemometrics Regression Tools." Technometrics, 35(2):109-135 (1993).
8. Jordan, M. I., Ghahramani, Z., Jaakkola, T. S., and Saul, L. K. An introduction to variational methods for graphical models. Cambridge, MA, USA: MIT Press (1999).
9. Park, T. and Casella, G. "The Bayesian Lasso." Journal of the American Statistical Association, 103:681-686(6) (2008).
10. Tibshirani, R. "Regression Shrinkage and Selection via the Lasso." Journal of the Royal Statistical Society. Series B (Methodological), 58(1):267-288 (1996).
11. West, M. "Outlier Models and Prior Distributions in Bayesian Linear Regression." Journal of the Royal Statistical Society. Series B (Methodological), 46(3):431-439 (1984).
12. West, M. "On Scale Mixtures of Normal Distributions." Biometrika, 74(3):646-648 (1987).
13. Yuan, M. and Lin, Y. "Efficient Empirical Bayes Variable Selection and Estimation in Linear Models." Journal of the American Statistical Association, 100(472):1215-1225 (2005).
14. Zhao, P. and Yu, B. "On Model Selection Consistency of Lasso." J. Mach. Learn. Res., 7 (2006).
15. Zou, H. "The Adaptive Lasso and Its Oracle Properties." Journal of the American Statistical Association, 101:1418-1429 (2006).