Загрузка...
Snuba: Automating Weak Supervision to Label Training Data
As deep learning models are applied to increasingly diverse problems, a key bottleneck is gathering enough high-quality training labels tailored to each task. Users therefore turn to weak supervision, relying on imperfect sources of labels like pattern matching and user-defined heuristics. Unfortuna...
Сохранить в:
| Опубликовано в: : | Proceedings VLDB Endowment |
|---|---|
| Главные авторы: | , |
| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
2018
|
| Предметы: | |
| Online-ссылка: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6879381/ https://ncbi.nlm.nih.gov/pubmed/31777681 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.14778/3291264.3291268 |
| Метки: |
Добавить метку
Нет меток, Требуется 1-ая метка записи!
|