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...
In this paper, we introduce a novel discriminative feature space which is efficient not only for face detection but also for recognition. The face representation is based on local...
Background: Predicting a protein’s structural class from its amino acid sequence is a fundamental problem in computational biology. Much recent work has focused on developing ne...
Iain Melvin, Eugene Ie, Rui Kuang, Jason Weston, W...
This paper proposes a new approach for classifying multivariate time-series with applications to the problem of writer independent online handwritten character recognition. Each t...
Recently, the margin criterion has been successfully used for parameter optimization in graphical models. We introduce maximum margin based structure learning for Bayesian network...