Data Partition and Rate Control for Learning and Energy Efficient Edge Intelligence

Author:

Li Xiaoyang1ORCID,Wang Shuai2ORCID,Zhu Guangxu3ORCID,Zhou Ziqin1ORCID,Huang Kaibin4ORCID,Gong Yi1ORCID

Affiliation:

1. Department of Electrical and Electronic Engineering, Southern University of Science and Technology, Shenzhen, China

2. Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China

3. Shenzhen Research Institute of Big Data, Shenzhen, China

4. Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

China Postdoctoral Science Foundation

Basic and Applied Basic Research Foundation of Guangdong Province

Youth Innovative Talent Project

Fellowship Award from the Research Grants Council of the Hong Kong Special Administrative Region under Grant HKU

Hong Kong Research Grants Council

Innovation and Technology Fund

Shenzhen Science and Technology Program

Open Research Fund from the Guangdong Laboratory of Artificial Intelligence and Digital Economy

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Applied Mathematics,Electrical and Electronic Engineering,Computer Science Applications

Reference46 articles.

1. Data partition and rate control for learning and energy efficient edge intelligence;li;arXiv 2107 08884,2021

2. Edge Learning With Unmanned Ground Vehicle: Joint Path, Energy, and Sample Size Planning

3. Predicting accuracy on large datasets from smaller pilot data

4. Speeding up automatic hyperparameter optimization of deep neural networks by extrapolation of learning curves;domhan;Proc AAAI Conf Artif Intell,2015

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