We develop a new component analysis framework, the Noisy-Or Component Analyzer (NOCA), that targets high-dimensional binary data. NOCA is a probabilistic latent variable model tha...
Feature selection aims to reduce dimensionality for building comprehensible learning models with good generalization performance. Feature selection algorithms are largely studied ...
We propose a novel framework for contour based object
detection and recognition, which we formulate as a joint
contour fragment grouping and labeling problem. For a
given set of...
ChengEn Lu, Longin Jan Latecki, Nagesh Adluru, Hai...
This paper presents a mathematical framework for the evaluation of the performance of proactive and reactive routing protocols in mobile ad hoc networks (MANETs). This unified fram...
Hui Xu, Xianren Wu, Hamid R. Sadjadpour, J. J. Gar...
- We present a comprehensive UML statechart diagram analysis framework. This framework allows one to progressively perform different analysis operations to analyze UML statechart d...