Foundational optimization algorithms are the core driving force behind deep learning, evolving from early stochastic gradient descent (SGD) to the widely adopted Adam family. However, as the scale of ...

PRIMA is a package for solving general nonlinear optimization problems without using derivatives. It provides the reference implementation of Powell's derivative-free optimization methods, i.e., ...

Google said this week that its research on a new compression method could reduce the amount of memory required to run large language models by six times. SK Hynix, Samsung and Micron shares fell as ...

If Google’s AI researchers had a sense of humor, they would have called TurboQuant, the new, ultra-efficient AI memory compression algorithm announced Tuesday, “Pied Piper” — or, at least that’s what ...

Abstract: With the increasing industrial deployment of robotic arms, the society is in urgent need of research on autonomous path planning of robotic arms. In this paper, firstly, its coordinate ...

Traditional approaches to analytical method optimization (e.g., univariate and “guess-and-check”) can be time-consuming, costly, and often fail to identify true optima within the parameter space.

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 the easiest pieces first. But this kind of sorting has a cost.

The National Capital Planning Commission has become pivotal in the administration’s campaign to discredit Jerome H. Powell, the chair of the Federal Reserve. By Alan Rappeport Reporting from ...

Abstract: Displacements estimated from two ultrasound echo signals acquired before and after applying quasi-static external forces can be utilized to generate strain images for ultrasound elastography ...