Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with pseudo-inverse training implemented using JavaScript. Compared to other training techniques, such as ...

Abstract: Nonnegative low-rank matrix approximation is an important technique in data analysis for extracting meaningful patterns from high-dimensional nonnegative data. This nonnegative low-rank ...

Abstract: Whereas on many motorways, traffic operations are permanently monitored, and long historical logs of such data exist, they are not directly usable for lane change studies, as they only ...

Lasso is a regularization method for parameter estimation in linear models. It optimizes the model parameters with respect to a loss function subject to model complexities. This paper explores the use ...

All methods which include treatment of relativistic effects are ultimately based on the Dirac equation, which has a four component wave function. The solutions to the Dirac equation describe both ...

This project provides a comprehensive framework for understanding and comparing ALL approaches to sequential decision-making, from uninformed search algorithms to modern reinforcement learning and ...