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Tree Planar Languages
2007
Seventh IEEE International Conference on Data Mining Workshops (ICDMW 2007)
Planar languages offer an alternative to grammars and automata for representing languages. They are based on hyperplanes in a feature space associated with a string kernel, which corresponds to a set of linear equalities over features. This makes planar languages inherently learnable, in the sense of being identifiable in the limit from positive data, i.e. learnable in an unsupervised setting, even under strong constraints on the learner's behaviour and on computational resources used. The
doi:10.1109/icdmw.2007.82
dblp:conf/icdm/Florencio07
fatcat:4hxpyexajbc2hjfe2r3zwjubgu