A two sample test in high dimensional data MS Srivastava, S Katayama, Y Kano
Journal of Multivariate Analysis 114, 349-358, 2013
160 2013 Asymptotic distributions of some test criteria for the mean vector with fewer observations than the dimension S Katayama, Y Kano, MS Srivastava
Journal of Multivariate Analysis 116, 410-421, 2013
26 2013 Lasso penalized model selection criteria for high-dimensional multivariate linear regression analysis S Katayama, S Imori
Journal of Multivariate Analysis 132, 138-150, 2014
12 2014 Sparse and robust linear regression: An optimization algorithm and its statistical properties S Katayama, H Fujisawa
Statistica Sinica, 1243-1264, 2017
10 2017 A new test on high-dimensional mean vector without any assumption on population covariance matrix S Katayama, Y Kano
Communications in Statistics-Theory and Methods 43 (24), 5290-5304, 2014
9 2014 Robust and sparse Gaussian graphical modelling under cell‐wise contamination S Katayama, H Fujisawa, M Drton
Stat 7 (1), e181, 2018
8 2018 Positive-definite modification of a covariance matrix by minimizing the matrix norm with applications to portfolio optimization S Cho, S Katayama, J Lim, YG Choi
AStA Advances in Statistical Analysis 105 (4), 601-627, 2021
2 2021 Computational and statistical analyses for robust non-convex sparse regularized regression problem S Katayama
Journal of Statistical Planning and Inference 201, 20-31, 2019
2 2019 Apparel Item Recommendation using Graph Regularized Nonnegative Tensor Factorization K Tazawa, K Neichi, Y Ohara, K Chikuma, S Katayama, K Nakata
Tokyo Institute of Technology Department of Industrial Engineering and …, 2017
1 2017 High-dimensional mean estimation via ℓ1 penalized normal likelihood S Katayama
Journal of Multivariate Analysis 130, 90-106, 2014
1 2014 Corrigendum to" A two sample test in high dimensional data"[J. Multivariate Anal. 114 (2013) 349-358] MS Srivastava, S Katayama, Y Kano
Journal of Multivariate Analysis 119, 209, 2013
1 2013 Adaptively Robust and Sparse K-means Clustering H Li, S Sugasawa, S Katayama
arXiv preprint arXiv:2407.06945, 2024
2024 Hypothesis testing on high dimensional parameter under confounding S Katayama
Direct estimation of conditional averaging treatment effect in high dimensions S Katayama
SEMINAR S Katayama
Screening and Selection Methods in High-Dimensional Linear Regression Model S Imori, K Shota, W Hirofumi