Papers by Huan Ling

1 papers
Adversarial Contrastive Estimation (P18-1)

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Challenge: Noise contrastive estimation (NCE) is a general strategy used in word embeddings and translations for knowledge graphs.
Approach: They propose to augment negative sampler into mixture distribution with adversarially learned sampler and to combine it with noise contrastive estimation (NCE) they observe faster convergence and improved results on multiple metrics.
Outcome: The proposed model performs better on word embeddings, order embedds and knowledge graph embeddments and faster convergence and improved results on multiple metrics.

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