Deep Networks With Large Output Spaces

international conference on learning representations, 2014.

Cited by: 31|Bibtex|Views154
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Other Links: dblp.uni-trier.de|academic.microsoft.com|arxiv.org

Abstract:

Deep neural networks have been extremely successful at various image, speech, video recognition tasks because of their ability to model deep structures within the data. However, they are still prohibitively expensive to train and apply for problems containing millions of classes in the output layer. Based on the observation that the key...More

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