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Theory reconstruction: a representation learning view on predicate invention
Published 28 Jun 2016 in stat.ML, cs.LG, and cs.LO | (1606.08660v2)
Abstract: With this positional paper we present a representation learning view on predicate invention. The intention of this proposal is to bridge the relational and deep learning communities on the problem of predicate invention. We propose a theory reconstruction approach, a formalism that extends autoencoder approach to representation learning to the relational settings. Our intention is to start a discussion to define a unifying framework for predicate invention and theory revision.
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