A Grammar-Based Approach to Visual Category Learning
نویسندگان
چکیده
In this paper, we investigate one-shot learning in the context of artificial categories with abstract structural characteristics. We propose a grammar-based approach to structure representation, which allows us to treat visual category learning as an instance of grammar induction. We provide a model of one-shot learning as Bayesian inference over hypotheses, where grammars are hypotheses and learning amounts to picking the best grammar.
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تاریخ انتشار 2008