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 ...

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 ...

Function secret sharing (FSS) is a secret sharing technique for functions in a specific function class, mainly including distributed point function (DPF) and distributed comparison function (DCF). As ...

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 ...

Learn how gradient descent really works by building it step by step in Python. No libraries, no shortcuts—just pure math and code made simple. Donald Trump's Epstein problem keeps coming back Michael ...

Abstract: Distributed gradient descent algorithms have come to the fore in modern machine learning, especially in parallelizing the handling of large datasets that are distributed across several ...

ABSTRACT: As drivers age, roadway conditions may become more challenging, particularly when normal aging is coupled with cognitive decline. Driving during lower visibility conditions, such as ...