Shanhao Han

Maintaining Fairness in Logit-based Knowledge Distillation for Class-Incremental Learning

Logit-based knowledge distillation (KD) is commonly used to mitigate catastrophic forgetting in class-incremental learning (CIL) caused by data distribution shifts. However, the strict match of logit values between student and teacher models conflicts with the cross-entropy (CE) loss objective of le…