machine learning algorithms are even less straightforward than nonlinear regression, partly because machine learning dispenses with the constraint of fitting to a specific mathematical function ...

Opinion: Lidiya Mishchenko and Pooya Shoghi explain how to bridge a gap preventing successful patent claims to protect new ...

Previous methods struggle to incorporate real-time data or account for nonlinear interactions among macroeconomic variables.

Machine learning algorithms learn from data to solve problems that are too complex to solve with conventional programming. ... The pooling layer performs a form of non-linear down-sampling.

A new machine learning approach tries to better emulate the human brain, in hopes of creating more capable agentic AI.

They employed a machine-learning algorithm called reservoir computing to “learn” the dynamics of an archetypal chaotic system called the Kuramoto-Sivashinsky equation. ... and in order not to run away ...