An Optimized Design Technique of Low-bit Neural Network Training for Personalization on IoT Devices

Author:

Choi Seungkyu1,Shin Jaekang1,Choi Yeongjae1,Kim Lee-Sup1

Affiliation:

1. School of Electrical Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea

Funder

National Research Foundation of Korea

Samsung Advanced Institute of Technology

Publisher

ACM

Cited by 13 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A review of on-device machine learning for IoT: An energy perspective;Ad Hoc Networks;2024-02

2. Accelerating On-Device DNN Training Workloads via Runtime Convergence Monitor;IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems;2023-05

3. Energy-Efficient Federated Training on Mobile Device;IEEE Network;2023

4. Energy-Efficient CNN Personalized Training by Adaptive Data Reformation;IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems;2023-01

5. EVE;Proceedings of the 41st IEEE/ACM International Conference on Computer-Aided Design;2022-10-30

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