| 研究課題/領域番号 |
22K17877
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| 研究機関 | 東北大学 |
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研究代表者 |
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| 研究期間 (年度) |
2022-04-01 – 2026-03-31
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| キーワード | Distributed Learning / Machine Learning / Computation Offloading / Satellite Networks / UAV Networks / Quantum Learning |
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| 研究実績の概要 |
This year, 5 papers were published, including two international conference papers. Progress was made in multiple directions. First, an important paper was published that explains how Digital Twins can be used for multiple applications, including the distributed training of learning models. Two papers were published explaining how deployed servers in satellites and aerial vehicles can help with distributed processing and distributed learning. One paper was published explaining how changes in the environment can impact the learning models. Finally, the use of quantum learning in distributed drone systems was also evaluated.
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| 現在までの達成度 (区分) |
現在までの達成度 (区分)
1: 当初の計画以上に進展している
理由
Work has progressed well in training Machine Learning and in using Distributed Learning. I also recruited two international exchange students that have been phenomenal in helping out with the results of this project.
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| 今後の研究の推進方策 |
For the future, the implementation and use of Federated Learning models, especially in satellite environments, is scheduled.
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| 次年度使用額が生じた理由 |
The materials bought were slightly cheaper than anticipated, so there is a bit of leftover funds.
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