This work addresses the problem of finding the adjustable parameters of a learning algorithm using Genetic Algorithms. This problem is also known as the model selection problem. In...
— A key step in many statistical learning methods used in machine learning involves solving a convex optimization problem containing one or more hyper-parameters that must be sel...
Kristin P. Bennett, Jing Hu, Xiaoyun Ji, Gautam Ku...
Model-based segmentation approaches, such as those employing Active Shape Models (ASMs), have proved to be useful for medical image segmentation and understanding. To build the mo...
Current work in object categorization discriminates
among objects that typically possess gross differences
which are readily apparent. However, many applications
require making ...
Andrew Moldenke, Asako Yamamuro, David A. Lytle, E...