Latent Variable Models (LVM), like the Shared-GPLVM
and the Spectral Latent Variable Model, help mitigate over-
fitting when learning discriminative methods from small or
modera...
Many approaches to learning classifiers for structured objects (e.g., shapes) use generative models in a Bayesian framework. However, state-of-the-art classifiers for vectorial d...
Most approaches to learn classifiers for structured objects (e.g., images) use generative models in a classical Bayesian framework. However, state-of-the-art classifiers for vecto...
The symmetrical decomposition is a powerful method to extract features for image recognition. It reveals the significant discriminative information from the mirror image of symmetr...
In this paper, we derive a data mining framework to analyze 3D features on human faces. The framework leverages kernel density estimators, genetic algorithm and an information com...
Sreenivas R. Sukumar, Hamparsum Bozdogan, David L....