Deep Hash Embedding for Large-Vocab Categorical Feature Representations

Wang-Cheng Kang
Wang-Cheng Kang
Derek Zhiyuan Cheng
Derek Zhiyuan Cheng
Tiansheng Yao
Tiansheng Yao
Cited by: 0|Bibtex|Views19
Other Links: arxiv.org

Abstract:

Embedding learning for large-vocabulary categorical features (e.g. user/item IDs, and words) is crucial for deep learning, and especially neural models for recommendation systems and natural language understanding tasks. Typically, the model creates a huge embedding table that each row represents a dedicated embedding vector for every f...More

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