Use of semantic content is one of the major issues which needs to be addressed for improving image retrieval effectiveness. We present a new approach to classify images based on t...
Low-dimensional topic models have been proven very useful for modeling a large corpus of documents that share a relatively small number of topics. Dimensionality reduction tools s...
Feature subset selection is important not only for the insight gained from determining relevant modeling variables but also for the improved understandability, scalability, and pos...
We introduce a regularized kernel-based rule for unsupervised change detection based on a simpler version of the recently proposed kernel Fisher discriminant ratio. Compared to ot...
For supervised learning, feature selection algorithms attempt to maximise a given function of predictive accuracy. This function usually considers the ability of feature vectors t...