In this paper we integrate two essential processes, discretization of continuous data and learning of a model that explains them, towards fully computational machine learning from...
We propose a general method to watermark and probabilistically identify the structured outputs of machine learning algorithms. Our method is robust to local editing operations and...
Ashish Venugopal, Jakob Uszkoreit, David Talbot, F...
We present and discuss several spatiotemporal kernels designed to mine real-life and simulated data in support of drought prediction. We implement and empirically validate these k...
— Feature selection and ensemble classification increase system efficiency and accuracy in machine learning, data mining and biomedical informatics. This research presents an ana...