The Commonality-Based Crossover Framework has been presented as a general model for designing problem specific operators. Following this model, the Common Features/Random Sample ...
Stephen Y. Chen, Cesar Guerra-Salcedo, Stephen F. ...
Variable selection problems are typically addressed under a penalized optimization framework. Nonconvex penalties such as the minimax concave plus (MCP) and smoothly clipped absol...
Many learning applications are characterized by high dimensions. Usually not all of these dimensions are relevant and some are redundant. There are two main approaches to reduce d...
We developed measures relating feature vector distributions to speaker recognition (SR) performances for performance prediction and potential arbitrary data selection for SR. We ex...
Feature selection for unsupervised tasks is particularly challenging, especially when dealing with text data. The increase in online documents and email communication creates a nee...
Nirmalie Wiratunga, Robert Lothian, Stewart Massie