Corpus ID: 4992154

Learning Word Representations with Hierarchical Sparse Coding

@article{Yogatama2015LearningWR,
  title={Learning Word Representations with Hierarchical Sparse Coding},
  author={Dani Yogatama and Manaal Faruqui and Chris Dyer and Noah A. Smith},
  journal={ArXiv},
  year={2015},
  volume={abs/1406.2035}
}
  • Dani Yogatama, Manaal Faruqui, +1 author Noah A. Smith
  • Published 2015
  • Computer Science, Mathematics
  • ArXiv
  • We propose a new method for learning word representations using hierarchical regularization in sparse coding inspired by the linguistic study of word meanings. We show an efficient learning algorithm based on stochastic proximal methods that is significantly faster than previous approaches, making it possible to perform hierarchical sparse coding on a corpus of billions of word tokens. Experiments on various benchmark tasks---word similarity ranking, analogies, sentence completion, and… CONTINUE READING
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