ABSTRACT: Artificial deep neural networks (ADNNs) have become a cornerstone of modern machine learning, but they are not immune to challenges. One of the most significant problems plaguing ADNNs is ...

Section 1. Purpose. From the founding of our Republic, scientific discovery and technological innovation have driven American progress and prosperity. Today, America is in a race for global technology ...

A vital ingredient for making quantum computers truly useful just might be conventional computers. That was the message from a gathering of researchers this month, which explained that classical ...

A.I. has added urgency to the U.S. national laboratories that have been sites of cutting-edge scientific research, leading to deals with tech giants like Nvidia to speed up. A.I. has added urgency to ...

The original version of this story appeared in Quanta Magazine. If you want to solve a tricky problem, it often helps to get organized. You might, for example, break the problem into pieces and tackle ...

Abstract: The increasing scale and complexity of modern power systems impose higher demands for the secure and stable operation of power grids. Traditional methods for identifying key transmission ...

HSBC on Thursday announced it has successfully used quantum computing in a trial to optimize bond trading, making it the first in the world to prove the value of the powerful emerging technology in ...

Abstract: Traditional Stochastic Gradient Descent (SGD) follows a sequential update process, which can be slow and inefficient for large-scale distributed learning tasks. Parallel computing offers a ...

Dr. James McCaffrey presents a complete end-to-end demonstration of the kernel ridge regression technique to predict a single numeric value. The demo uses stochastic gradient descent, one of two ...

What just happened? Normal Computing, a young company founded by alumni of Google Brain, Google X, and Palantir, has introduced what it calls a new era in computing. The startup announced the ...