32 citations · 122 across the 21 of their papers we have counts for
3 papers · 1 filter
MetaPerturb: Transferable Regularizer for Heterogeneous Tasks and Architectures
Jeongun Ryu, Jaewoong Shin, Hae Beom Lee +1
Regularization and transfer learning are two popular techniques to enhance generalization on unseen data, which is a fundamental problem of machine learning. Regularization techniq…
Meta-Learning for Short Utterance Speaker Recognition with Imbalance Length Pairs
Seong Min Kye, Youngmoon Jung, Hae Beom Lee +2
In practical settings, a speaker recognition system needs to identify a speaker given a short utterance, while the enrollment utterance may be relatively long. However, existing sp…
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…