We present a new approach to the supervised learning of lateral interactions for the competitive layer model (CLM) dynamic feature binding architecture. The method is based on con...
Abstract: Kernel classifiers based on Support Vector Machines (SVM) have achieved state-ofthe-art results in several visual classification tasks, however, recent publications and d...
Guo ShengYang, Min Tan, Si-Yao Fu, Zeng-Guang Hou,...
Background: Designing appropriate machine learning methods for identifying genes that have a significant discriminating power for disease outcomes has become more and more importa...
The formalism of probabilistic graphical models provides a unifying framework for capturing complex dependencies among random variables, and building large-scale multivariate stat...
In this paper, a multiobjective (MO) learning approach to image feature extraction is described, where Pareto-optimal interest point (IP) detectors are synthesized using genetic p...