nips nips2003 nips2003-172 nips2003-172-reference knowledge-graph by maker-knowledge-mining

172 nips-2003-Semi-Supervised Learning with Trees


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Author: Charles Kemp, Thomas L. Griffiths, Sean Stromsten, Joshua B. Tenenbaum

Abstract: We describe a nonparametric Bayesian approach to generalizing from few labeled examples, guided by a larger set of unlabeled objects and the assumption of a latent tree-structure to the domain. The tree (or a distribution over trees) may be inferred using the unlabeled data. A prior over concepts generated by a mutation process on the inferred tree(s) allows efficient computation of the optimal Bayesian classification function from the labeled examples. We test our approach on eight real-world datasets. 1


reference text

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