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We consider the problem of aligning continuous word representations, learned in multiple languages, to a common space.
A generalized solution of the orthogonal procrustes problem
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On the use of gromov-hausdorff distances for shape comparison
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Ronan Collobert, Jason Weston, Léon Bottou, Michael Karlen, Koray Kavukcuoglu, and Pavel Kuksa · 2011
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Kernel hyperalignment
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Georgiana Dinu, Angeliki Lazaridou, and Marco Baroni · 2014
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Filippo Santambrogio · 2015
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Learning bilingual word embeddings with (almost) no bilingual data
Mikel Artetxe, Gorka Labaka, and Eneko Agirre · 2017
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Word translation without parallel data
Alexis Conneau, Guillaume Lample, Marc’Aurelio Ranzato, Ludovic Denoyer, and Hervé Jégou · 2017
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Knowledge distillation for bilingual dictionary induction
Ndapandula Nakashole and Raphael Flauger · 2017
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Computational optimal transport
Gabriel Peyré, Marco Cuturi, et al · 2017
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Offline bilingual word vectors, orthogonal transformations and the inverted softmax
Samuel L Smith, David HP Turban, Steven Hamblin, and Nils Y Hammerla · 2017
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Entropic metric alignment for correspondence problems
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Gromov-wasserstein alignment of word embedding spaces
David Alvarez-Melis and Tommi Jaakkola · 2018
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