Improving Word Embedding Using Variational Dropout
Pre-trained word embeddings are essential in natural language processing (NLP). In recent years, many post-processing algorithms have been proposed to improve the pre-trained word embeddings. We present a novel method - Orthogonal Auto Encoder with Variational Dropout (OAEVD) for improving word embe...
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| Autores principales: | , , , |
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| Formato: | Artigo |
| Lenguaje: | Inglês |
| Publicado: |
LibraryPress@UF
2023-05-01
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| Colección: | Proceedings of the International Florida Artificial Intelligence Research Society Conference |
| Materias: | |
| Acceso en línea: | https://journals.flvc.org/FLAIRS/article/view/133326 |
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