— Many real-world applications have problems when learning from imbalanced data sets, such as medical diagnosis, fraud detection, and text classification. Very few minority clas...
This paper presents a method for analyzing the Bit Error Rate of recovered data for PLL-based data recovery systems (DRS) as the PLL comes into lock. This method is based on the a...
Background: This paper addresses key biological problems and statistical issues in the analysis of large gene expression data sets that describe systemic temporal response cascade...
: This paper addresses the sparse data problem in the linear regression model, namely the number of variables is significantly larger than the number of the data points for regress...
We analyze a neural network model of the Eriksen task, a twoalternative forced choice task in which subjects must correctly identify a central stimulus and disregard flankers that...