Using error decay prediction to overcome practical issues of deep active learning for named entity recognition

DOI10.1007/s10994-020-05897-1OpenAlexW3047430695MaRDI QIDQ2217437

Sunil Mohan, Shankar Vembu, Rheeya Uppaal, Haw-Shiuan Chang, Andrew Kachites McCallum

Publication date: 29 December 2020

Published in: Machine Learning (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1911.07335

zbMATH Keywords

clusteringactive learningtransparencyblack-box modelsnamed entity recognitionrobustness to labeling noise

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Uses Software

• tn
• word2vec

Cites Work

• Two faces of active learning
• Newton-Type Minimization via the Lanczos Method
• On the hardness of approximating minimization problems
• Unnamed Item
• Unnamed Item
• Unnamed Item

This page was built for publication: Using error decay prediction to overcome practical issues of deep active learning for named entity recognition