36 citations · 98 across the 26 of their papers we have counts for
26 papers
Uniform Convergence of Deep Neural Networks with Lipschitz Continuous Activation Functions and Variable Widths
Yuesheng Xu, Haizhang Zhang
We consider deep neural networks with a Lipschitz continuous activation function and with weight matrices of variable widths. We establish a uniform convergence analysis framework…
Sparse Representer Theorems for Learning in Reproducing Kernel Banach Spaces
Rui Wang, Yuesheng Xu, Mingsong Yan
Sparsity of a learning solution is a desirable feature in machine learning. Certain reproducing kernel Banach spaces (RKBSs) are appropriate hypothesis spaces for sparse learning m…
Successive Affine Learning for Deep Neural Networks
Yuesheng Xu
This paper introduces a successive affine learning (SAL) model for constructing deep neural networks (DNNs). Traditionally, a DNN is built by solving a non-convex optimization prob…
A Non-gradient DG method for second-order Elliptic Equations in the Non-divergence Form
Weifeng Qiu, Jin Ren, Ke Shi +1
based optimization is widely used in image denoising, machine learning and related applications. One of the main features of such approach is that it naturally provide a spar…
Multi-Grade Deep Learning
Yuesheng Xu
The current deep learning model is of a single-grade, that is, it learns a deep neural network by solving a single nonconvex optimization problem. When the layer number of the neur…
Fast Multiscale Functional Estimation in Optimal EMG Placement for Robotic Prosthesis Controllers
Jin Ren, Guohui Song, Lucia Tabacu +1
Electrocardiogram (EMG) signals play a significant role in decoding muscle contraction information for robotic hand prosthesis controllers. Widely applied decoders require large am…