IEEE

On the Convergence, Implicit Bias, and Edge of Stability of Gradient Descent in Deep Learning: Reviewing recent progress [Special Issue on the Mathematics of Deep Learning]

Abstract: Deep neural networks (DNNs) trained via gradient descent (GD) with random initialization and without any regularization enjoy good generalization performance in practice despite being highly ...
BBC

Module 8 (M8) – Algebra – Graphs

Before reading this guide, you may find it helpful to read the guide on graphs from Module 7 (M7) and the guide on indices from Module 8 (M8). In Module 7 (M7) Graphs, you learned that simultaneous ...
ucdavis.edu

Applied Mathematics

The Applied Mathematics Graduate Group is an interdisciplinary group of over 90 faculty and is recognized for the mathematical rigor of its programs and its dynamic research atmosphere. The program is ...
JSTOR Daily

The College Mathematics Journal

This title is part of a longer publication history. The full run of this journal will be searched. TITLE HISTORY A title history is the publication history of a journal and includes a listing of the ...
IEEE

A Decentralized Proximal-Gradient Method With Network Independent Step-Sizes and Separated Convergence Rates

Abstract: This paper proposes a novel proximal-gradient algorithm for a decentralized optimization problem with a composite objective containing smooth and nonsmooth terms. Specifically, the smooth ...
National Council of Teachers of Mathematics

Browse All Grants

Apply for NCTM's Mathematics Education Trust grants, scholarships, and awards. Funding is available to help math teachers, prospective teachers, and other math educators improve the teaching and ...