Understanding Homoskedasticity in Regression Modeling With Examples

Discover the importance of homoskedasticity in regression models, where error variance is constant, and explore examples that illustrate this key concept.
IEEE

Federated Function-on-function Regression with an Efficient Gradient Boosting Algorithm for Privacy-Preserving Telemedicine

Abstract: Federated Learning (FL) is an emerging computing paradigm to collaboratively train Machine Learning (ML) models across multi-source data while preserving privacy. The major challenge of ...
rocketswire.usatoday

Defensive regression: Rockets, Alperen Sengun searching for answers

HOUSTON -- With 7 points on just 3-of-11 shooting (27.3%), Rockets center Alperen Sengun struggled offensively in Thursday’s home loss to the Hornets. And against Charlotte, Sengun also went through ...
IEEE

Gradient-Aware Loss Function for Improved Learning in Speech Enhancement

Abstract: Conventional loss functions for gradient descent are designed mainly to assess output quality, with limited attention to gradient behavior. This study identifies the gradient inconsistency ...