An MCMC-based method of comparing connectionist models in cognitive science

Date

2004

Authors

Woojae, K.
Navarro, D.
Pitt, M.
Myung, J.

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Conference paper

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Advances in neural information processing systems 16: proceedings of the 2003 conference / Sebastian Thrun, Lawrence K. Saul, and Bernhard Schölkopf (eds.): pp.937-944

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Woojae Kim, Daniel J. Navarro, Mark A. Pitt, In Jae Myung

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Conference on Neural Information Processing Systems (2003 : Vancouver, Canada)

Abstract

Despite the popularity of connectionist models in cognitive science, their performance can often be difficult to evaluate. Inspired by the geometric approach to statistical model selection, we introduce a conceptually similar method to examine the global behavior of a connectionist model, by counting the number and types of response patterns it can simulate. The Markov Chain Monte Carlo-based algorithm that we constructed nds these patterns efficiently. We demonstrate the approach using two localist network models of speech perception.

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