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Popular pages
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Publications | Rémi Lebret
Deep Learning / AI / NLP
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Word Embeddings for Natural Language Processing | Rémi Lebret
Abstract Word embedding is a feature learning technique which aims at mapping words from a vocabulary into vectors of real numbers in a low-dimensional space. By leveraging large corpora of unlabeled ...
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Word Embeddings through Hellinger PCA | Rémi Lebret
Abstract Word embeddings resulting from neural language models have been shown to be a great asset for a large variety of NLP tasks. However, such architecture might be difficult and time-consuming to...
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Rmixmod: A MIXture MODelling R package | Rémi Lebret
Abstract Mixmod is a well-established software package for fitting mixture models of multivariate Gaussian or multinomial probability distribution functions to a given dataset with either a clustering...
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Phrase-based Image Captioning | Rémi Lebret
Abstract Generating a novel textual description of an image is an interesting problem that connects computer vision and natural language processing. In this paper, we present a simple model that is ab...
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Neural Text Generation from Structured Data with Application to the Biography Domain | Rémi Lebret
Abstract This paper introduces a neural model for concept-to-text generation that scales to large, rich domains. We experiment with a new dataset of biographies from Wikipedia that is an order of magn...