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佐藤 光哉 研究室
Showing the original Japanese · View translation
無線ネットワークと時空間統計で、分散データを活かす研究室。
AboutAbout the lab
分散データを活かす、次世代の無線と統計。
佐藤光哉研究室は、
研究室の
研究室の
Key terms
- ガウス過程
- 観測した
データから、 観測していない 点の 値を、 不確かさの 幅つきで 推定する 統計の 手法 - ベイズ最適化
- 試した
結果を もとに 次に 試す条件を 選び、 少ない 試行で 良い 設定を 探す方 法 - 分散機械学習
- データや
計算を 複数の 端末や機器に 分けて、 機械学習を 行う 方法
NewsLab news
修士課程の
学生が、 ITU AI/ML in 5G Challenge 2025 で 最優秀賞を 受賞 論文が
IEEE Transactions on Cognitive Communications and Networking に 採択 修士課程の
学生が、 令和6年度電気通信大学 学生表彰を 受賞 修士課程の
学生が、 IEICE RISING2024 で 優秀ポスター発表賞を 受賞
ResearchResearch themes
佐藤光哉研究室は、
MembersFaculty
佐藤光哉研究室の
- Associate Professor佐藤 光哉
VoicesStudent voices
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Report an errorAbout the images
The top and research theme images are illustrative and were not taken at the lab. They are cropped from Wikimedia Commons images. Cropped CC BY-SA images are provided under the same CC BY-SA license as the original (version shown on each line).
- Top image: “WSN event detection” Camackay10 / CC BY-SA 4.0 (cropped)
- Related lab (策力木格 研究室): “Traffic information sign, M2, Belfast - geograph.org.uk - 3854949” Albert Bridge / CC BY-SA 2.0 (cropped)
- Related lab (本多 弘樹・三輪 忍・八巻 隼人 研究室): “Network switches” ShakataGaNai / CC BY-SA 3.0 (cropped)
- Related lab (幸島 匡宏 研究室): “Machine Learning cookies” Syced / CC0 (cropped)
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