To fully realize the benefits of partial and rapid reconfiguration of field-programmable devices, we often need to dynamically schedule computing tasks and generate instance-sp...
Active learning methods seek to reduce the number of labeled examples needed to train an effective classifier, and have natural appeal in spam filtering applications where trustwo...
Abstract--High-dimensional data are common in many domains, and dimensionality reduction is the key to cope with the curse-of-dimensionality. Linear discriminant analysis (LDA) is ...
Long-term persistent tracking in ever-changing environments is a challenging task, which often requires addressing difficult object appearance update problems. To solve them, most...
: We propose a new nonparametric family of oscillation heuristics for improving linear classifiers in the two-group discriminant problem. The heuristics are motivated by the intuit...