Joint optimization of energy consumption and completion time in federated learning

• Main Authors: Zhou, Xinyu, Zhao, Jun, Han, Huimei, Guet, Claude
• 其他作者: School of Physical and Mathematical Sciences
• 格式: Conference or Workshop Item
• 語言: English
• 出版: 2022
• 主題: Engineering::Computer science and engineering; Federated Learning; Frequency-Division Multiple Access; Resource Allocation
• 在線閱讀: https://hdl.handle.net/10356/159471
• 機構: Nanyang Technological University

Federated Learning (FL) is an intriguing distributed machine learning approach due to its privacy-preserving characteristics. To balance the trade-off between energy and execution latency, and thus accommodate different demands and application scenarios, we formulate an optimization problem to minim...