Perspectives on sparse bayesian learning

Advances in Neural Information Processing Systems

Volumn , Issue , 2004, Pages

  Wipf, David ^a   Palmer, Jason ^a   Rao, Bhaskar ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DUAL FORM; FULL MODEL; HYPERPARAMETERS; MARGINALIZATION; RELEVANCE VECTOR MACHINE; SPARSE BAYESIAN LEARNING; SPARSE BAYESIAN LEARNING (SBL); VARIATIONAL APPROXIMATION;

EID: 33748908922     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (7)

1. C. Bishop and M. Tipping, "Variational relevance vector machines, " Proc. 16th Conf. Uncertainty in Artificial Intelligence, pp. 46-53, 2000.
2. R. Duda, P. Hart, and D. Stork, Pattern Classification, Wiley, Inc., New York, 2nd ed., 2001.
3. A.C. Faul and M.E. Tipping, "Analysis of sparse Bayesian learning, " Advances in Neural Information Processing Systems 14, pp. 383-389, 2002.
4. M. Girolami, "A variational method for learning sparse and overcomplete representations, " Neural Computation, vol. 13, no. 11, pp. 2517-2532, 2001.
5. M.I. Jordan, Z. Ghahramani, T. Jaakkola, and L.K. Saul, "An introduction to variational methods for graphical models, " Machine Learning, vol. 37, no. 2, pp. 183-233, 1999.
6. D.J.C. MacKay, "Bayesian interpolation, " Neural Comp., vol. 4, no. 3, pp. 415-447, 1992.
7. M.E. Tipping, "Sparse Bayesian learning and the relevance vector machine, " Journal of Machine Learning, vol. 1, pp. 211-244, 2001.