3 papers
eess.AS2020
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…
cs.LG2020
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…
cs.LG2019
Learning to Generalize to Unseen Tasks with Bilevel Optimization
Hayeon Lee, Donghyun Na, Hae Beom Lee +1
Recent metric-based meta-learning approaches, which learn a metric space that generalizes well over combinatorial number of different classification tasks sampled from a task distr…