IEEE

Uniform Convergence of Deep Neural Networks With Lipschitz Continuous Activation Functions and Variable Widths

Abstract: We consider deep neural networks (DNNs) with a Lipschitz continuous activation function and with weight matrices of variable widths. We establish a uniform convergence analysis framework in ...
GitHub

Uniform Convergence of Lipschitz Functions with Dependent Gaussian Samples

This repository contains the research paper and code related to Uniform Convergence of Lipschitz Functions with Dependent Gaussian Samples. The work provides theoretical bounds for learning Lipschitz ...
JSTOR Daily

Convergence of Polynomial Level Sets

In this paper we give a characterization of pointwise and uniform convergence of sequences of homogeneous polynomials on a Banach space by means of the convergence of their level sets. Results are ...
JSTOR Daily

Uniform convergence of the empirical cumulative distribution function under informative selection from a finite population

This is a preview. Log in through your library . Abstract Consider informative selection of a sample from a finite population. Responses are realized as independent and identically distributed (i.i.d.
IEEE

Uniform Convergence of Lipschitz Functions with Dependent Gaussian Samples

Abstract: In many practical learning problems, training samples are not i.i.d., and there is an intrinsic dependency among samples. Therefore, theoretical study of learning with dependent data has ...
Scientific Research Publishing

Operator Convergence and the Structure of Physical Reality: Weak, Strong, and Uniform Limits as Models of Field, Mass, and Gravitation ()

We investigate bounded linear operators on separable Hilbert spaces and their convergence properties. We provide connections between uniform, strong, and weak convergence modes and interpret them in ...