Learning with Noisy Labels
- Studying with Dr. Zhaozheng Yin the problem of learning under the presence of noisy labels within an image dataset.
- Mitigating ways in which a robust model can be built so as to be tolerable to overfitting caused by noisy data.
- Utilizing semi-supervised learning by treating noisy samples as unlabeled in order to compete with state-of-the-art.