284 citations
- LG (South Korea)KR3 papers
- Seoul National UniversityKR3 papers
- Yonsei UniversityKR2 papers
- California Southern UniversityUS1 paper
- CHA University Bundang Medical CenterKR1 paper
- Instituto Tecnológico de CanariasES1 paper
- Jilin UniversityCN1 paper
- Korea Advanced Institute of Science and TechnologyKR1 paper
- Kyonggi UniversityKR1 paper
- LG AI Research (South Korea)KR1 paper
- Microsoft (United States)US1 paper
- Norwegian University of Science and TechnologyNO1 paper
Showing 2020Show all
2 papers · 1 filter
cs.LG2020★ 3 cited
Message Passing Adaptive Resonance Theory for Online Active Semi-supervised Learning
Taehyeong Kim, Injune Hwang, Hyundo Lee +4
Active learning is widely used to reduce labeling effort and training time by repeatedly querying only the most beneficial samples from unlabeled data. In real-world problems where…
cs.CL2020★ 4 cited
Deep Active Learning for Sequence Labeling Based on Diversity and Uncertainty in Gradient
Yekyung Kim
Recently, several studies have investigated active learning (AL) for natural language processing tasks to alleviate data dependency. However, for query selection, most of these stu…