Analyzing human feature learning as nonparametric Bayesian inference

Advances in Neural Information Processing Systems 21 - Proceedings of the 2008 Conference

Volumn , Issue , 2009, Pages 97-104

  Austerweil, Joseph L ^a   Griffiths, Thomas L ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BAYESIAN NETWORKS; INFERENCE ENGINES; LEARNING SYSTEMS;

ALGORITHM MODEL; BAYESIAN STATISTICS; COGNITIVE MODEL; FEATURE LEARNING; HUMAN PERCEPTUAL SYSTEM; MACHINE LEARNING ALGORITHMS; NON-PARAMETRIC BAYESIAN; NON-PARAMETRIC BAYESIAN INFERENCES; RATIONAL MODELS; SENSORY DATA;

LEARNING ALGORITHMS;

EID: 84858761439     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (15)

1. P. G. Schyns, R. L. Goldstone, and J. Thibaut. Development of features in object concepts. Behavioral and Brain Sciences, 21:1-54, 1998.
2. R. L. Goldstone. Learning to perceive while perceiving to learn. In Perceptual organization in vision: Behavioral and neural perspectives, pages 233-278. 2003.
3. I. Biederman and M. M. Schiffrar. Sexing day-old chicks: A case study and expert systems analysis of a difficult perceptual-learning task. Journal of Experimental Psychology: Learning, Memory, and Cognition, 13:640-645, 1987.
4. M. L. Minsky and S. A. Papert. Perceptrons. MIT Press, Cambridge, MA, 1969.
5. B. Scholkopf and A. J. Smola. Learning with Kernels. MIT Press, Cambridge, MA, 2001.
6. J. R. Anderson. Is human cognition adaptive? Behavioral and Brain Sciences, 14:471-517, 1991.
7. A. N. Sanborn, T. L. Griffiths, and D. J. Navarro. A more rational model of categorization. In Proceedings of the 28th Annual Conference of the Cognitive Science Society, 2006.
8. T. L. Griffiths and Z. Ghahramani. Infinite latent feature models and the Indian buffet process. In Advances in Neural Information Processing Systems 18, 2006.
9. R. M. Shiffrin and N. Lightfoot. Perceptual learning of alphanumeric-like characters. In The psychology of learning and motivation, volume 36, pages 45-82. Academic Press, San Diego, 1997.
10. R. L. Goldstone. Influences of categorization on perceptual discrimination. Journal of Experimental Psychology: General, 123:178-200, 1994.
11. R. Pevtzow and R. L. Goldstone. Categorization and the parsing of objects. In Proceedings of the Sixteenth Annual Conference of the Cognitive Science Society, pages 712-722, Hillsdale, NJ, 1994. Lawrence Erlbaum Associates.
12. G. Orban, J. Fiser, R. N. Aslin, and M. Lengyel. Bayesian model learning in human visual perception. In Advances in Neural Information Processing Systems 18, 2006.
13. F. Wood, T. L. Griffiths, and Z. Ghahramani. A non-parametric Bayesian method for inferring hidden causes. In Proceeding of the 22nd Conference on Uncertainty in Artificial Intelligence, 2006.
14. F.Wood and T. L. Griffiths. Particle filtering for nonparametric Bayesian matrix factorization. In Advances in Neural Information Processing Systems 19, 2007.
15. R. Thibaux and M. I. Jordan. Hierarchical Beta processes and the Indian buffet process. Technical Report 719, University of California, Berkeley. Department of Statistics, 2006.