Abstract: This technical note deals with switched linear system identification and more particularly aims at solving switched linear regression problems in a large-scale setting with both numerous ...

The source code for the demo program is too long to be ... Now here's where the difficulty of linear support vector regression arises. The loss function is not calculus-differentiable, which means ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of neural network quantile regression. The goal of a quantile regression problem is to predict a single numeric ...

ABSTRACT: In this paper, the Automated Actuarial Loss Reserving Model is developed and extended using machine learning. The traditional actuarial reserving techniques are no longer compatible with the ...

I am working on implementing an additional "regression head" to the YOLOv8 segmentation model because I am dealing with a custom dataset which has 6 variables I want to predict in addition to the bbox ...

Deep neural networks for classification and regression tasks are trained with ... Washington(AlphaUpdater): A PID-like updater based on the code of Sunil Thulasidasan. notes ----- * All abstention ...