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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence, 35 / No. 3: AAAI-21 Technical Tracks 3

Progressive Network Grafting for Few-Shot Knowledge Distillation

February 1, 2023

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Authors

Chengchao Shen

Zhejiang University


Xinchao Wang

Stevens Institute of Technology


Youtan Yin

Zhejiang University


Jie Song

Zhejiang University


Sihui Luo

Zhejiang University


Mingli Song

Zhejiang University Alibaba-Zhejiang University Joint Research Institute of Frontier Technologies


DOI:

10.1609/aaai.v35i3.16356


Abstract:

Knowledge distillation has demonstrated encouraging performances in deep model compression. Most existing approaches, however, require massive labeled data to accomplish the knowledge transfer, making the model compression a cumbersome and costly process. In this paper, we investigate the practical few-shot knowledge distillation scenario, where we assume only a few samples without human annotations are available for each category. To this end, we introduce a principled dual-stage distillation scheme tailored for few-shot data. In the first step, we graft the student blocks one by one onto the teacher, and learn the parameters of the grafted block intertwined with those of the other teacher blocks. In the second step, the trained student blocks are progressively connected and then together grafted onto the teacher network, allowing the learned student blocks to adapt themselves to each other and eventually replace the teacher network. Experiments demonstrate that our approach, with only a few unlabeled samples, achieves gratifying results on CIFAR10,CIFAR100, and ILSVRC-2012. On CIFAR10 and CIFAR100, our performances are even on par with those of knowledge distillation schemes that utilize the full datasets. The source code is available at https://github.com/zju-vipa/NetGraft.

Topics: AAAI

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HOW TO CITE:

Chengchao Shen||Xinchao Wang||Youtan Yin||Jie Song||Sihui Luo||Mingli Song Progressive Network Grafting for Few-Shot Knowledge Distillation Proceedings of the AAAI Conference on Artificial Intelligence (2021) 2541-2549.

Chengchao Shen||Xinchao Wang||Youtan Yin||Jie Song||Sihui Luo||Mingli Song Progressive Network Grafting for Few-Shot Knowledge Distillation AAAI 2021, 2541-2549.

Chengchao Shen||Xinchao Wang||Youtan Yin||Jie Song||Sihui Luo||Mingli Song (2021). Progressive Network Grafting for Few-Shot Knowledge Distillation. Proceedings of the AAAI Conference on Artificial Intelligence, 2541-2549.

Chengchao Shen||Xinchao Wang||Youtan Yin||Jie Song||Sihui Luo||Mingli Song. Progressive Network Grafting for Few-Shot Knowledge Distillation. Proceedings of the AAAI Conference on Artificial Intelligence 2021 p.2541-2549.

Chengchao Shen||Xinchao Wang||Youtan Yin||Jie Song||Sihui Luo||Mingli Song. 2021. Progressive Network Grafting for Few-Shot Knowledge Distillation. "Proceedings of the AAAI Conference on Artificial Intelligence". 2541-2549.

Chengchao Shen||Xinchao Wang||Youtan Yin||Jie Song||Sihui Luo||Mingli Song. (2021) "Progressive Network Grafting for Few-Shot Knowledge Distillation", Proceedings of the AAAI Conference on Artificial Intelligence, p.2541-2549

Chengchao Shen||Xinchao Wang||Youtan Yin||Jie Song||Sihui Luo||Mingli Song, "Progressive Network Grafting for Few-Shot Knowledge Distillation", AAAI, p.2541-2549, 2021.

Chengchao Shen||Xinchao Wang||Youtan Yin||Jie Song||Sihui Luo||Mingli Song. "Progressive Network Grafting for Few-Shot Knowledge Distillation". Proceedings of the AAAI Conference on Artificial Intelligence, 2021, p.2541-2549.

Chengchao Shen||Xinchao Wang||Youtan Yin||Jie Song||Sihui Luo||Mingli Song. "Progressive Network Grafting for Few-Shot Knowledge Distillation". Proceedings of the AAAI Conference on Artificial Intelligence, (2021): 2541-2549.

Chengchao Shen||Xinchao Wang||Youtan Yin||Jie Song||Sihui Luo||Mingli Song. Progressive Network Grafting for Few-Shot Knowledge Distillation. AAAI[Internet]. 2021[cited 2023]; 2541-2549.


ISSN: 2374-3468


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