We present a new approach to semi-supervised anomaly detection. Given a set of training examples believed to come from the same distribution or class, the task is to learn a model ...
In this paper, active learning with support vector machines (SVMs) is applied to the problem of tornado prediction. This method is used to predict which storm-scale circulations yi...
Theodore B. Trafalis, Indra Adrianto, Michael B. R...
This paper presents an incremental and scalable learning algorithm in order to mine numeric, low dimensionality, high–cardinality, time–changing data streams. Within the Superv...
Although it has been studied for several years by computer vision and machine learning communities, image annotation is still far from practical. In this paper, we present AnnoSea...
Financial forecasting is the basis for budgeting activities and estimating future financing needs. Applying machine learning and data mining models to financial forecasting is both...