Traditionally, feature selection methods work directly on labeled examples. However, the availability of labeled examples cannot be taken for granted for many real world applications, such as medical diagnosis, forensic science, fraud detection, etc, where labeled examples are hard to find. This practical problem calls the need for “semi-supervised feature selection” to choose the optimal set o...

This paper defines and studies a variable selection procedure called Testing-Based Forward Model Selection. The procedure inductively selects covariates which increase predictive accuracy into a working statistical regression model until a stopping criterion is met. The stopping criteria and selection criteria are defined using statistical hypothesis tests. The paper explicitly describes a test...

A novel signaling scheme is presented, where a set of orthogonal signals is transmitted in parallel, which are selected according to the so-called residue number system (RNS). Hence the system is essentially a multiple code parallel communication scheme using high modulation alphabets. It is demonstrated that the system performance can be substantially improved by exploiting a number of advanta...