Compared to traditional statistical methods such as logistic regression, machine learning algorithms can effectively handle high-dimensional data and complex non-linear relationships, uncovering ...

SoFiE Financial Machine Learning Summer School "Financial Machine Learning" July 28 – August 1, 2025 The Society for Financial Econometrics (SoFiE) Summer School is an annual week-long research-based ...

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

This video is a one stop shop for understanding What is linear regression in machine learning. Linear regression in machine learning is considered as the basis or foundation in machine learning.

This study investigates how environmental factors impact photovoltaic systems’ outputs, through a one-year data collection. Nineteen machine learning linear regression models were employed to predict ...

There is a need for design strategies that can support rapid and widespread deployment of new energy systems and process technologies. In a previous work, we introduced process family design as an ...

Synopsis This work demonstrates a new approach to atmospheric inverse modeling of CO 2 emissions using Gaussian Process machine learning and modern probabilistic programming languages.

Additionally, machine learning is used to allow computer programmers to determine, without explicit programming, which of its applications—graphing, regression, and predicating is most closely related ...