Papers by Leila Wehbe

1 papers
Self-Discriminative Learning for Unsupervised Document Embedding (N19-1)

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Challenge: Existing methods for document embedding learning do not consider inter-document relationships.
Approach: They propose to exploit the inter-document information and directly model the relations of documents in embedding space with a discriminative network and a novel objective.
Outcome: The proposed method has errors that are 5 to 13% lower than state-of-the-art models and is even more pronounced in scarce label setting.

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