Sukmin Yun

Robust Inference via Generative Classifiers for Handling Noisy Labels

2019 · arXiv (Cornell University)

Large-scale datasets may contain significant proportions of noisy (incorrect) class labels, and it is well-known that modern deep neural networks (DNNs) poorly generalize from such noisy training datasets. To mitigate the issue, we propose a …

Regularizing Class-Wise Predictions via Self-Knowledge Distillation

2020

Deep neural networks with millions of parameters may suffer from poor generalization due to overfitting. To mitigate the issue, we propose a new regularization method that penalizes the predictive distribution between similar samples. In particular, …