Yinghuan Shi

MutexMatch: Semi-Supervised Learning with Mutex-Based Consistency Regularization

2022 · arXiv (Cornell University)

The core issue in semi-supervised learning (SSL) lies in how to effectively leverage unlabeled data, whereas most existing methods tend to put a great emphasis on the utilization of high-confidence samples yet seldom fully explore …

NormAUG: Normalization-guided Augmentation for Domain Generalization

2023 · arXiv (Cornell University)

Deep learning has made significant advancements in supervised learning. However, models trained in this setting often face challenges due to domain shift between training and test sets, resulting in a significant drop in performance during …

PLACE Dropout: A Progressive Layer-wise and Channel-wise Dropout for Domain Generalization

2023 · ACM Transactions on Multimedia Computing Communications and Applications

Domain generalization (DG) aims to learn a generic model from multiple observed source domains that generalizes well to arbitrary unseen target domains without further training. The major challenge in DG is that the model inevitably …