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Deep Clustering for Unsupervised Learning of Visual Features
Mathilde Caron, Piotr Bojanowski, Armand Joulin +1
Clustering is a class of unsupervised learning methods that has been extensively applied and studied in computer vision. Little work has been done to adapt it to the end-to-end tra…
Loss in Translation: Learning Bilingual Word Mapping with a Retrieval Criterion
Armand Joulin, Piotr Bojanowski, Tomas Mikolov +2
Continuous word representations learned separately on distinct languages can be aligned so that their words become comparable in a common space. Existing works typically solve a le…
Colorless green recurrent networks dream hierarchically
Kristina Gulordava, Piotr Bojanowski, Edouard Grave +2
Recurrent neural networks (RNNs) have achieved impressive results in a variety of linguistic processing tasks, suggesting that they can induce non-trivial properties of language. W…
Learning Word Vectors for 157 Languages
Edouard Grave, Piotr Bojanowski, Prakhar Gupta +2
Distributed word representations, or word vectors, have recently been applied to many tasks in natural language processing, leading to state-of-the-art performance. A key ingredien…