Toward Efficient Retraining: A Large-Scale Approximate Neural Network Framework With Cross-Layer Optimization-Reference-Cited by-同舟云学术

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Toward Efficient Retraining: A Large-Scale Approximate Neural Network Framework With Cross-Layer Optimization

Published:2024-06 Issue:6 Volume:32 Page:1004-1017
ISSN:1063-8210
Container-title:IEEE Transactions on Very Large Scale Integration (VLSI) Systems
language:
Short-container-title:IEEE Trans. VLSI Syst.

Author:

Yu Tianyang¹^ORCID,Wu Bi¹^ORCID,Chen Ke¹^ORCID,Yan Chenggang¹^ORCID,Liu Weiqiang¹^ORCID

Affiliation:

1. College of Integrated Circuits, Nanjing University of Aeronautics and Astronautics, Nanjing, China

Funder

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Natural Science Foundation of Jiangsu Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/92/10536717/10504795.pdf?arnumber=10504795

Reference41 articles.

1. Deep Residual Learning for Image Recognition

2. MobileNetV2: Inverted Residuals and Linear Bottlenecks

3. YOLO9000: Better, Faster, Stronger

4. Learning N: M fine-grained structured sparse neural networks from scratch;Zhou

5. Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference

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