— 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...
In our research on superimposed information management, we have developed applications where information elements in the superimposed layer serve to annotate, comment, restructure...
Sudarshan Murthy, David Maier, Lois M. L. Delcambr...
An image representation framework based on structured sparse model selection is introduced in this work. The corresponding modeling dictionary is comprised of a family of learned ...
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...
A new method for optimizing complex functions and systems is described that employs Learnable Evolution Model (LEM), a form of non-Darwinian evolutionary computation guided by mac...
Ryszard S. Michalski, Janusz Wojtusiak, Kenneth A....