Abstract: Nonconvex finite-sum optimization finds wide applications in various signal processing and machine learning tasks. The well-known stochastic gradient algorithms generate unbiased stochastic ...

Ashley has been writing about video games professionally for over eight years, but her path into gaming journalism wasn't exactly a straight line. She grew up playing games and got a Nintendo 64 when ...

Abstract: Optimization algorithms play an important role in the training of machine learning models. Gradient-based optimizers such as Adam, RMSprop, and Stochastic Gradient Descent (SGD) are widely ...

XRP has climbed 2.5% over the past 24 hours to trade at $1.44 at the time of writing, largely tracking a broader rebound across the cryptocurrency market led by Bitcoin (BTC). Looking ahead toward the ...

The CMS Collaboration has shown, for the first time, that machine learning can be used to fully reconstruct particle collisions at the LHC. This new approach can reconstruct collisions more quickly ...

XRP has lost some steam over the past twenty-four hours as the Senate delayed a key crypto market structure bill on January 15. At the same time, daily trading volume slipped 30% as the broader market ...

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 ...

As modern computing becomes limited by energy consumption, there is growing interest in physical computing paradigms that can operate closer to fundamental thermodynamic limits. Thermodynamic ...

This repository explores the concept of Orthogonal Gradient Descent (OGD) as a method to mitigate catastrophic forgetting in deep neural networks during continual learning scenarios. Catastrophic ...