CDFKD-MFS: Collaborative Data-Free Knowledge Distillation via Multi-Level Feature Sharing-Reference-Cited by-同舟云学术

CDFKD-MFS: Collaborative Data-Free Knowledge Distillation via Multi-Level Feature Sharing

Author:

Hao Zhiwei¹^ORCID,Luo Yong²,Wang Zhi³^ORCID,Hu Han¹^ORCID,An Jianping¹^ORCID

Affiliation:

1. School of Information and Electronics, Beijing Institute of Technology, Beijing, China

2. School of Computer Science, Wuhan University, and Hubei Luojia Laboratory, Wuhan, China

3. Shenzhen International Graduate School, Tsinghua University, Shenzhen, China

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Special Fund of Hubei Luojia Laboratory

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Media Technology,Signal Processing

Link

Reference61 articles.

3. Contrastive model inversion for data-free knowledge distillation;fang,2021

5. Zero-shot knowledge distillation in deep networks;nayak;Proc Int Conf Mach Learn,0

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