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Task’s Choice: Pruning-Based Feature Sharing (PBFS) for Multi-Task Learning
In most of the existing multi-task learning (MTL) models, multiple tasks’ public information is learned by sharing parameters across hidden layers, such as hard sharing, soft sharing, and hierarchical sharing. One promising approach is to introduce model pruning into information learning, such as sp...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8947268/ https://www.ncbi.nlm.nih.gov/pubmed/35327942 http://dx.doi.org/10.3390/e24030432 |