Papers with parameterizing embedding layers

1 papers
Tensorized Embedding Layers (2020.findings-emnlp)

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Challenge: Using the Tensor Train decomposition, embeddings layers occupy large portion of model weights, preventing their deployment in limited resource settings.
Approach: They propose a method for parameterizing embedding layers based on the Tensor Train decomposition, which allows compressing the model significantly at the cost of a negligible drop or even a slight gain in performance.
Outcome: The proposed method can be plugged into any model and trained end-to-end.

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