44 citations · 90 across the 6 of their papers we have counts for
3 papers · 1 filter
TiDAL: Learning Training Dynamics for Active Learning
Seong Min Kye, Kwanghee Choi, Hyeongmin Byun +1
Active learning (AL) aims to select the most useful data samples from an unlabeled data pool and annotate them to expand the labeled dataset under a limited budget. Especially, unc…
Learning with Noisy Labels by Efficient Transition Matrix Estimation to Combat Label Miscorrection
Seong Min Kye, Kwanghee Choi, Joonyoung Yi +1
Recent studies on learning with noisy labels have shown remarkable performance by exploiting a small clean dataset. In particular, model agnostic meta-learning-based label correcti…
Meta-Learned Confidence for Few-shot Learning
Seong Min Kye, Hae Beom Lee, Hoirin Kim +1
Transductive inference is an effective means of tackling the data deficiency problem in few-shot learning settings. A popular transductive inference technique for few-shot metric-b…