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In statistical relational learning, knowledge graph completion deals with automatically understanding the structure of large knowledge graphs---labeled directed graphs---and predicting missing relationships---labeled edges.
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A link prediction approach for item recommendation with complex numbers
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Learning structured embeddings of knowledge bases
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Embedding entities and relations for learning and inference in knowledge bases
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Sign rank versus vc dimension
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Global optimality of local search for low rank matrix recovery
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Combining two and three-way embedding models for link prediction in knowledge bases
Alberto Garcia-Duran, Antoine Bordes, Nicolas Usunier, and Yves Grandvalet · 2016
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Matrix completion has no spurious local minimum
Rong Ge, Jason D Lee, and Tengyu Ma · 2016
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Initial investigation of speech synthesis based on complex-valued neural networks
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Statistical relational artificial intelligence: Logic, probability, and computation
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Complex embeddings for simple link prediction
Théo Trouillon, Johannes Welbl, Sebastian Riedel, Éric Gaussier, and Guillaume Bouchard · 2016
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A factorization machine framework for testing bigram embeddings in knowledge base completion
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On the equivalence of holographic and complex embeddings for link prediction
Katsuhiko Hayashi and Masashi Shimbo · 2017
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Complex and holographic embeddings of knowledge graphs: a comparison
Théo Trouillon and Maximilian Nickel · 2017
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