Hi,
Thanks for sharing this code and it's really helpful.
Recently I read your paper:"MSD: Multi-Self-Distillation Learning via Multi-classifiers within Deep Neural Networks".It's a very interesting work and the results are much better than the paper "be your own teacher" which you reimplement here.
However,after reading your paper,I could just find some slight differences between this two papers:
1.the differences of bottleneck in the model.
2.some changes of hyper-parameter.
Is there some important details that I missed?And could you please tell me about the key difference between the two papers that lead to such a significant improvement?
Hi,
Thanks for sharing this code and it's really helpful.
Recently I read your paper:"MSD: Multi-Self-Distillation Learning via Multi-classifiers within Deep Neural Networks".It's a very interesting work and the results are much better than the paper "be your own teacher" which you reimplement here.
However,after reading your paper,I could just find some slight differences between this two papers:
1.the differences of bottleneck in the model.
2.some changes of hyper-parameter.
Is there some important details that I missed?And could you please tell me about the key difference between the two papers that lead to such a significant improvement?