3 papers
stat.ME2019
Learning partially ranked data based on graph regularization
Kento Nakamura, Keisuke Yano, Fumiyasu Komaki
Ranked data appear in many different applications, including voting and consumer surveys. There often exhibits a situation in which data are partially ranked. Partially ranked data…
math.ST2018
Minimax Predictive Density for Sparse Count Data
Keisuke Yano, Ryoya Kaneko, Fumiyasu Komaki
This paper discusses predictive densities under the Kullback--Leibler loss for high-dimensional Poisson sequence models under sparsity constraints. Sparsity in count data implies z…
math.ST2017
On -Admissibility in High Dimension and Nonparametrics
Keisuke Yano, Fumiyasu Komaki
In this paper, we discuss the use of -admissibility for estimation in high-dimensional and nonparametric statistical models. The minimax rate of convergence is widely…