78 citations · 412 across the 48 of their papers we have counts for
28 papers · 1 filter
Rates of Approximation by ReLU Shallow Neural Networks
Tong Mao, Ding-Xuan Zhou
Neural networks activated by the rectified linear unit (ReLU) play a central role in the recent development of deep learning. The topic of approximating functions from Hölder space…
Generalization Guarantees of Gradient Descent for Multi-Layer Neural Networks
Puyu Wang, Yunwen Lei, Di Wang +2
Recently, significant progress has been made in understanding the generalization of neural networks (NNs) trained by gradient descent (GD) using the algorithmic stability approach.…
Sketching with Spherical Designs for Noisy Data Fitting on Spheres
Shao-Bo Lin, Di Wang, Ding-Xuan Zhou
This paper proposes a sketching strategy based on spherical designs, which is applied to the classical spherical basis function approach for massive spherical data fitting. We cond…
Generalization Analysis for Contrastive Representation Learning
Yunwen Lei, Tianbao Yang, Yiming Ying +1
Recently, contrastive learning has found impressive success in advancing the state of the art in solving various machine learning tasks. However, the existing generalization analys…
SignReLU neural network and its approximation ability
Jianfei Li, Han Feng, Ding-Xuan Zhou
Deep neural networks (DNNs) have garnered significant attention in various fields of science and technology in recent years. Activation functions define how neurons in DNNs process…
Approximation analysis of CNNs from a feature extraction view
Jianfei Li, Han Feng, Ding-Xuan Zhou
Deep learning based on deep neural networks has been very successful in many practical applications, but it lacks enough theoretical understanding due to the network architectures…