The automatic annotation of images presents a particularly complex problem for machine learning researchers. In this work we experiment with semantic models and multi-class learnin...
Large amounts of remotely sensed data calls for data mining techniques to fully utilize their rich information content. In this paper, we study new means of discovery and summariz...
Abstract. Analysis of data without labels is commonly subject to scrutiny by unsupervised machine learning techniques. Such techniques provide more meaningful representations, usef...
Surveillance systems have long been used to monitor industrial processes and are becoming increasingly popular in public health and anti-terrorism applications. Most early detecti...
We consider the problem of numerical stability and model density growth when training a sparse linear model from massive data. We focus on scalable algorithms that optimize certain...