Sample-based Regularization: A Transfer Learning Strategy Toward Better Generalization

no code implementations • 10 Jul 2020 • Yunho Jeon, Yongseok Choi, Jaesun Park, Subin Yi, Dong-Yeon Cho, Jiwon Kim

However, this is likely to restrict the potential of the target model and some transferred knowledge from the source can interfere with the training procedure.

Transfer Learning

Domain-Agnostic Few-Shot Classification by Learning Disparate Modulators

no code implementations • ICLR 2020 • Yongseok Choi, Junyoung Park, Subin Yi, Dong-Yeon Cho

Although few-shot learning research has advanced rapidly with the help of meta-learning, its practical usefulness is still limited because most of them assumed that all meta-training and meta-testing examples came from a single domain.

Classification Few-Shot Learning +2

Discriminative Few-Shot Learning Based on Directional Statistics

no code implementations • 5 Jun 2019 • Junyoung Park, Subin Yi, Yongseok Choi, Dong-Yeon Cho, Jiwon Kim

Metric-based few-shot learning methods try to overcome the difficulty due to the lack of training examples by learning embedding to make comparison easy.

Few-Shot Learning General Classification

Grouped Convolutional Neural Networks for Multivariate Time Series

no code implementations • 29 Mar 2017 • Subin Yi, Janghoon Ju, Man-Ki Yoon, Jaesik Choi

In experiments with two real-world datasets, we demonstrate that our group CNNs outperform existing CNN based regression methods.

Anomaly Detection Clustering +2