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Abstract: This study investigates a multi-task estimation under joint sparsity. We consider estimating multiple functions when functions of interest share common sparsity patterns. An $\ell _{2}$ ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of Nadaraya-Watson kernel regression using the C# language. NW kernel regression is simple to implement and is ...

ABSTRACT: Function-on-scalar regression is a type of function response regression used to analyze the relationship between function response and a set of scalar predictor factors. The variable ...

ABSTRACT: In this work, we seek the relationship between the order of the polynomial model and the number of knots and intervals that we need to fit the splines regression model. Regression models ...

Houses a series of projects I worked on for a course in Data Mining that I took in my Ph.D. Data Science program at UTEP in the Fall of 2022. Covers areas such as Regularized Logistic Regression, ...

This paper critically examines ‘kitchen sink regression’, a practice characterised by the manual or automated selection of variables for a multivariable regression model based on p values or ...

Abstract: Channel aging poses a huge challenge for the MU-MIMO (Multi-user Multiple-Input-Multiple Output) communications. To alleviate the problem, channel prediction is widely regarded as a ...