Rule-Enhanced Active Learning for Semi-Automated Weak Supervision

A major bottleneck preventing the extension of deep learning systems to new domains is the prohibitive cost of acquiring sufficient training labels. Alternatives such as weak supervision, active learning, and fine-tuning of pretrained models reduce this burden but require substantial human input to...

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Detalles Bibliográficos
Autores principales: Kartchner, David, Nakajima An, Davi, Ren, Wendi, Zhang, Chao, Mitchell, Cassie S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9281613/
https://www.ncbi.nlm.nih.gov/pubmed/35845102
http://dx.doi.org/10.3390/ai3010013

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9281613/
https://www.ncbi.nlm.nih.gov/pubmed/35845102
http://dx.doi.org/10.3390/ai3010013

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