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|Title:||Combining dimensions and features in similarity-based representations|
|Citation:||Advances in neural information processing systems 15: proceedings of the 2002 conference / Suzanna Becker, Sebastian Thrun and Klaus Obermayer (eds.): pp.67-74|
|Publisher Place:||United States|
|Conference Name:||Neural Information Processing Systems. Conference (16th : 2002 : British Columbia)|
|Daniel J. Navarro; Michael D. Lee|
|Abstract:||This paper develops a new representational model of similarity data that combines continuous dimensions with discrete features. An algorithm capable of learning these representations is described, and a Bayesian model selection approach for choosing the appropriate number of dimensions and features is developed. The approach is demonstrated on a classic data set that considers the similarities between the numbers 0 through 9.|
|Appears in Collections:||Aurora harvest 2|
Environment Institute publications
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