56 citations · 205 across the 38 of their papers we have counts for
4 papers · 1 filter
Hypothesis Test and Confidence Analysis with Wasserstein Distance on General Dimension
Masaaki Imaizumi, Hirofumi Ota, Takuo Hamaguchi
We develop a general framework for statistical inference with the 1-Wasserstein distance. Recently, the Wasserstein distance has attracted considerable attention and has been widel…
Improved Generalization Bounds of Group Invariant / Equivariant Deep Networks via Quotient Feature Spaces
Akiyoshi Sannai, Masaaki Imaizumi, Makoto Kawano
Numerous invariant (or equivariant) neural networks have succeeded in handling invariant data such as point clouds and graphs. However, a generalization theory for the neural netwo…
Adaptive Approximation and Generalization of Deep Neural Network with Intrinsic Dimensionality
Ryumei Nakada, Masaaki Imaizumi
In this study, we prove that an intrinsic low dimensionality of covariates is the main factor that determines the performance of deep neural networks (DNNs). DNNs generally provide…
On Random Subsampling of Gaussian Process Regression: A Graphon-Based Analysis
Kohei Hayashi, Masaaki Imaizumi, Yuichi Yoshida
In this paper, we study random subsampling of Gaussian process regression, one of the simplest approximation baselines, from a theoretical perspective. Although subsampling discard…