Jae‐Pil Heo

Regularization with Multiple Feature Combination for Few-Shot Learning

2021

Few-shot learning solves problems with a limited amount of labeled examples. Our analysis shows the existing metric-based methods concentrate on highly discriminative features while not fully utilizing whole capacity. In this work, we propose a …

Tailoring Self-Supervision for Supervised Learning

2022 · arXiv (Cornell University)

Recently, it is shown that deploying a proper self-supervision is a prospective way to enhance the performance of supervised learning. Yet, the benefits of self-supervision are not fully exploited as previous pretext tasks are specialized …