3 papers
stat.ML2025
Optimal Convergence Rates of Deep Neural Network Classifiers
Zihan Zhang, Lei Shi, Ding-Xuan Zhou
In this paper, we study the binary classification problem on under the Tsybakov noise condition (with exponent ) and the compositional assumption. This…
cs.LG2025
Super-fast Rates of Convergence for Neural Network Classifiers under the Hard Margin Condition
Nathanael Tepakbong, Xiang Zhou, Ding-Xuan Zhou
We study the classical binary classification problem for hypothesis spaces of Deep Neural Networks (DNNs) under Tsybakov's low-noise condition with exponent , as well as its l…
stat.ML2025
Two-Dimensional Deep ReLU CNN Approximation for Korobov Functions: A Constructive Approach
Qin Fang, Lei Shi, Min Xu +1
This paper investigates approximation capabilities of two-dimensional (2D) deep convolutional neural networks (CNNs), with Korobov functions serving as a benchmark. We focus on 2D…