3 papers
math.ST2026
Statistical learnability of smooth boundaries via pairwise binary classification with deep ReLU networks
Hiroki Waida, Takafumi Kanamori
The topic of nonparametric estimation of smooth boundaries is extensively studied in the conventional setting where pairs of single covariate and response variable are observed. Ho…
stat.ML2024
Investigating Self-Supervised Image Denoising with Denaturation
Hiroki Waida, Kimihiro Yamazaki, Atsushi Tokuhisa +2
Self-supervised learning for image denoising problems in the presence of denaturation for noisy data is a crucial approach in machine learning. However, theoretical understanding o…
stat.ML2024
Scaling-based Data Augmentation for Generative Models and its Theoretical Extension
Yoshitaka Koike, Takumi Nakagawa, Hiroki Waida +1
This paper studies stable learning methods for generative models that enable high-quality data generation. Noise injection is commonly used to stabilize learning. However, selectin…