Yijun Qu

Meta-Learning Dynamic Center Distance: Hard Sample Mining for Learning with Noisy Labels

The sample selection approach is a widely adopted strategy for learning with noisy labels, where examples with lower losses are effectively treated as clean during training. However, this clean set often becomes dominated by easy examples, limiting the model's meaningful exposure to more challenging…