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A generalization from string to trees and from languages to translations is given of the classical result that any regular language can be learned from examples: it is shown that for any deterministic top-down tree transformation there exists a sample set of polynomial size (with respect to the minimal transducer) which allows to infer the translation. Until now, only for string transducers and for simple relabeling tree transducers, similar results had been known. Learning of deterministicdoi:10.1145/1807085.1807122 dblp:conf/pods/LemayMN10 fatcat:fylbbdxjzbgm7npfnvsw326kja