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スラヴァキス研究室
Showing the original Japanese · View translation
データの幾何学的な構造を活かす、信号処理と機械学習の研究室。
AboutAbout the lab
データに潜む幾何学的な構造を活かす。
スラヴァキス研究室は、
信号や
強化学習、
研究には
Key terms
- 強化学習
- 試行錯誤で
得られる 報酬を もとに、 よい 行動の 選び方を コンピュータに 学ばせる 機械学習の 方法 - スパース
- データの
成分の ほとんどが 0で、 0でない 成分が わずかしかない こと - 多様体
- 曲面のように、
狭い 範囲で 見ると 平らな 空間とみなせる 図形や 空間
NewsLab news
オンライン強化学習の
論文を arXiv で 公開 論文が
国際会議 Asilomar Conference に 採択 テンソルトレインを
使った カーネル回帰の 論文を arXiv で 公開 鈴木助教の
非凸スパース強化学習の 論文を arXiv で 公開 強化学習の
論文が 国際会議 EUSIPCO 2026 に 採択
ResearchResearch themes
信号処理と
*Illustrative image新しい強化学習のアルゴリズム
状態や
*Illustrative imageスパース最適化の偏りを減らす
ほとんどの
*Illustrative image多様体の上での回帰
低次元の
*Illustrative imageリーマン多様体上のデータ分類
距離を
MembersFaculty
スラヴァキス研究室の
- Professorスラヴァキス コンスタンティノス
- Assistant Professor鈴木 京平Publications ↗
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: “The manifold paths of biology ( )” UCL Mathematical & Physical Sciences / CC BY 2.0 (cropped)
- 新しい
強化学習の アルゴリズム: “Atlas frontview 2013” DARPA / Public domain (cropped) - スパース最適化の
偏りを 減らす: “Orthogonal Matching Pursuit” Jacopo Bertolotti / CC0 (cropped) - 多様体の
上での 回帰: “Cardiac mri slice bionerd” Bionerd / CC BY-SA 3.0 (cropped) - リーマン多様体上の
データ分類: “The Human Connectome” Andreashorn / CC BY-SA 4.0 (cropped) - Related lab (篠﨑研究室): “Human voice spectrogram” Dvortygirl, Mysid / CC BY-SA 3.0 (cropped)
- Related lab (奥村・船越研究室): “Network visualisation incorporating sentiment analysis of the subreddit 'skeptic' from Reddit” Siobhán Grayson / CC BY-SA 4.0 (cropped)
- Related lab (山田研究室): “SAR Kilauea topo interferogram” JPL / Public domain (cropped)
- Related lab (黒田研究室): “Cosine Series Plus Noise TFM” Fourier1789 / CC BY-SA 4.0 (cropped)
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