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Translating Embeddings for Modeling Multi-relational Data

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Translating Embeddings for ModelingMulti-relational DataAntoine Bordes, Nicolas Usunier, Alberto Garcia-Dur anUniversit e de Technologie de Compi`egne CNRSHeudiasyc UMR 7253Compi`egne, France{bordesan, nusunier, Weston, Oksana YakhnenkoGoogle111 8th avenueNew York, NY, USA{jweston, consider the problem of embedding entities and relationships of Multi-relational data in low-dimensional vector spaces. Our objective is to propose acanonical model which is easy to train, contains a reduced number of parametersand can scale up to very large databases.}}

The optimization is carried out by stochastic gradient descent (in minibatch mode), over the possible h;‘ and t, with the additional constraints that the L 2-norm of the embeddings of the entities is 1 (no regularization or norm constraints are given to the label embeddings ‘).This constraint is important

  Descent, Embedding, Derating, Gradient descent

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