IEEE

Identification of Continuous-Time Linear Parameter Varying Systems With Noisy Scheduling Variable Using Local Regression

Abstract: Some nonlinear systems can be represented through linear parameter varying models. In this work, we address the estimation of continuous-time linear ...
Visual Studio Magazine

Kernel Ridge Regression with Cholesky Inverse Training Using C#

Dr. James McCaffrey presents a complete end-to-end demonstration of the kernel ridge regression technique to predict a single ...
The Diplomat

The Variables of OPCON: One Wartime OPCON Transition, Multiple Plans

Gen. Xavier T. Brunson, United Nations Command, Combined Forces Command, and United States Forces Korea Commanding General, and Republic of Korea Army Brig. Gen. Won-Jun Cha, Commander of Combined ...
IEEE

ŶUGO: Enhancing Power Consumption Predictions in Data Centers through Combined Multiple Linear Regression and Gradient Boosting Techniques on Hypervisor Load

Abstract: Accurate power consumption prediction in data centers is critical for optimizing energy efficiency, but is fundamentally challenged by workloads exhibiting both linear and non-linear ...
GitHub

Vision-Language Gradient Descent-driven All-in-One Deep Unfolding Networks

Abstract: Dynamic image degradations, including noise, blur and lighting inconsistencies, pose significant challenges in image restoration, often due to sensor limitations or adverse environmental ...