ホーム > 矢田和善/ Yata, Kazuyoshi

矢田和善

Yata, Kazuyoshi

数理物質系 , 教授
Institute of Pure and Applied Sciences , Professor

オープンアクセス版の論文は「つくばリポジトリ」で読むことができます。

1. Automatic Sparse PCA for High-Dimensional Data Yata, Kazuyoshi; Aoshima, Makoto
Statistica Sinica 35: 1069 (2025) Semantic Scholar
2. 高次元統計解析で探る銀河の分子ガスの物理状態と天文学への展望竹内, 努; 矢田, 和善; 江頭, 健斗; 青嶋, 誠 (+9 著者) 河野, 孝太郎
Proceedings of the Institute of Statistical Mathematics 72: 273 (2024)
3. Proposing a Low-Rank Approximation Method with Mathematical Guarantees for High-Dimensional Tensor Data HASEGAWA, Hiroki; YATA, Kazuyoshi; OKADA, Yukihiko; KUNIMATSU, Jun
Prceedings of 2024 IEEE International Conference on Big Data (BigData) 34 (2024) Semantic Scholar
4. Noise Reduced Common PCA for High-Dimensional, Low-Sample Size Multi-View Data Hasegawa, Hiroki; Kawamura, Homura; Shin, Ryota; Yata, Kazuyoshi (+1 著者) Kunimatsu, Jun
Proceedings of the 6th International Conference on Statistics: Theory and Applications (2024)
5. High Dimensional Statistical Analysis and its Application to an ALMA Map of NGC 253 Takeuchi; Tsutomu T.; Yata, Kazuyoshi; Egashira, Kento (+5 著者) Kono, Kai T.
The Astrophysical Journal Supplement Series 271: 44 (2024) Semantic Scholar
6. Asymptotic Properties of Hierarchical Clustering in High-Dimensional Settings Egashira, Kento; Yata, Kazuyoshi; Aoshima, Makoto
Journal of Multivariate Analysis 199: 105251 (2024) Semantic Scholar
7. Test for High-Dimensional Outliers with Principal Component Analysis Nakayama, Yugo; Yata, Kazuyoshi; Aoshima, Makoto
Japanese Journal of Statistics and Data Science Epub: (2024) Semantic Scholar
8. 階層的クラスタリングの高次元漸近的性質について江頭健斗; 矢田, 和善; 青嶋誠
数理解析研究所講究録 2221: 30 (2022)
9. Consistency of the objective general index in high-dimensional settings Takuma, Bando; Tomonari, Sei; Yata, Kazuyoshi
Journal of Multivariate Analysis 189: 104938 (2022) Semantic Scholar
10. Geometric classifiers for high-dimensional noisy data (Editor's invited paper) Ishii, Aki; Yata, Kazuyoshi; Aoshima, Makoto
Special Issue: 50th Anniversary Jubilee Edition, Journal of Multivariate Analysis 188: 104850 (2022)
11. Geometric classifiers for high-dimensional noisy data (Editor's invited paper) Ishii, Aki; Yata, Kazuyoshi; Aoshima, Makoto
Special Issue: 50th Anniversary Jubilee Edition, Journal of Multivariate Analysis 188: 104850 (2022) Semantic Scholar
12. Clustering by principal component analysis with Gaussian kernel in high-dimension, low-sample-size settings Nakayama, Yugo; Yata, Kazuyoshi; Aoshima, Makoto
JOURNAL OF MULTIVARIATE ANALYSIS 185: 104779 (2021) Semantic Scholar
13. Asymptotic properties of distance-weighted discrimination and its bias correction for high-dimension, low-sample-size data Egashira, Kento; Yata, Kazuyoshi; Aoshima, Makoto
JAPANESE JOURNAL OF STATISTICS AND DATA SCIENCE 4: 821 (2021) Semantic Scholar
14. Hypothesis tests for high-dimensional covariance structures Ishii, Aki; Yata, Kazuyoshi; Aoshima, Makoto
Annals of the Institute of Statistical Mathematics 73: 599 (2021) Semantic Scholar
15. Hypothesis tests for high-dimensional covariance structures Ishii, Aki; Yata, Kazuyoshi; Aoshima, Makoto
Annals of the Institute of Statistical Mathematics 73: 599 - 622 (2021) Semantic Scholar
16. 論説：高次元小標本における統計的仮説検定青嶋, 誠; 石井, 晶; 矢田和善
数学 73: 360 (2021)
17. 高次元におけるDistanceWeighted Discriminationについて江頭健斗; 矢田和善; 青嶋誠
数理解析研究所講究録 1 (2020)
18. High-dimensional covariance matrix estimation under the SSE model Konishi, Keisuke; Yata, Kazuyoshi; Aoshima, Makoto
数理解析研究所講究録 11 (2020)
19. Tests for high-dimensional covariance structures under the non-strongly spiked eigenvalue model Ishii, Aki; Yata, Kazuyoshi; Aoshima, Makoto
数理解析研究所講究録 21 (2020)
20. 単一強スパイク固有値モデルにおける高次元平均ベクトルの2標本検定石井晶; 矢田和善; 青嶋誠
応用統計学 49: 109 (2020)

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1. 高次元の統計学青嶋, 誠; 矢田, 和善
共立出版 2019年4月 (ISBN: 9784320112636)

1. Asymptotic properties of high-dimensional kernel PCA and its applications Nakayama, Yugo; Yata, Kazuyoshi; Aoshima, Makoto
International Symposium on New Developments of Theories and Methodologies for Large Complex Data 2021年11月6日招待有り
2. Sparse PCA for high-dimensional data based on the noise-reduction methodology and its application Yata, Kazuyoshi; Aoshima, Makoto
The 63rd ISI World Statistics Congress 2021年7月14日招待有り
3. Clustering by kernel PCA with Gaussian kernel and tuning for high-dimensional data Nakayama, Yugo; Yata, Kazuyoshi; Aoshima, Makoto
The 4th International Conference on Econometrics and Statistics 2021年6月26日招待有り
4. Tests for covariance structures in high-dimensional data Yata, Kazuyoshi; Ishii, Aki; Aoshima, Makoto
The 4th International Conference on Econometrics and Statistics 2021年6月26日招待有り
5. High-dimensional classifiers under the strongly spiked eigenvalue model Ishii, Aki; Yata, Kazuyoshi; Aoshima, Makoto
The 4th International Conference on Econometrics and Statistics 2021年6月25日招待有り
6. High-dimensional quadratic classifiers under the strongly spiked eigenvalue model Ishii, Aki; Yata, Kazuyoshi; Aoshima, Makoto
IISA 2021 Conference 2021年5月21日招待有り
7. 高次元におけるカーネル主成分分析の漸近的性質と異常値の検出への応用中山優吾; 矢田和善; 青嶋誠
日本数学会年度年会 2021年3月16日
8. 距離加重判別分析の高次元漸近的性質江頭健斗; 矢田和善; 青嶋誠
日本数学会年度年会 2021年3月16日
9. 高次元固有ベクトルの検定について石井晶; 矢田, 和善; 青嶋誠
日本数学会秋季総合分科会 2020年9月24日
10. Clustering by kernel principal component analysis for high-dimensional data 中山優吾; 矢田和善; 青嶋誠
日本数学会秋季総合分科会 2020年9月24日
11. 高次元データにおける距離加重判別分析の漸近的性質とバイアス補正江頭健斗; 矢田和善; 青嶋誠
統計関連学会連合大会 2020年9月11日
12. 高次元小標本における異常値の検出中山優吾; 矢田和善; 青嶋誠
統計関連学会連合大会 2020年9月10日
13. Tests of high-dimensional correlation matrices under the strongly spiked eigenvalue model 石井晶; 矢田和善; 青嶋誠
統計関連学会連合大会 2020年9月10日
14. 高次元スパースPCAの一致性とその応用矢田和善; 青嶋誠
統計関連学会連合大会 2020年9月10日
15. Tests for high-dimensiomal covariance structures under the SSE model Ishii, Aki; Yata, Kazuyoshi; Aoshima, Makoto
International Symposium on Theories and Methodologies for Large Complex Data 2019年11月21日招待有り
16. Inference on mean vectors for high-dimensional data with the strongly spiked eigenstructure Ishii, Aki; Yata, Kazuyoshi; Aoshima, Makoto
The 3rd International Conference on Econometrics and Statistics 2019年6月26日招待有り
17. A high-dimensional quadratic classifier by data transformation for strongly spiked eigenvalue models Yata, Kazuyoshi; Ishii, Aki; Aoshima, Makoto
The 3rd International Conference on Econometrics and Statistics 2019年6月26日招待有り
18. A high-dimensional quadratic classifier under the strongly spiked eigenvalue model Yata, Kazuyoshi; Ishii, Aki; Aoshima, Makoto
The 14th Workshop on Stochastic Models, Statistics and their Application 2019年3月6日招待有り
19. Tests of High-Dimensional Mean Vectors and Its Application Under the SSE Model Ishii, Aki; Yata, Kazuyoshi; Aoshima, Makoto
Waseda International Symposium “Introduction of General Causality to Various Data & its Applications” 2019年2月26日招待有り
20. Tests of high-dimensional mean vectors under the SSE model Ishii, Aki; Yata, Kazuyoshi; Aoshima, Makoto
International Symposium on Statistical Theory and Methodology for Large Complex Data 2018年11月26日招待有り