This paper proposes a method for computing fast approximations to support vector decision functions in the field of object detection. In the present approach we are building on an...
Data-intensive parallel applications on clouds need to deploy large data sets from the cloud's storage facility to all compute nodes as fast as possible. Many multicast algori...
Tatsuhiro Chiba, Mathijs den Burger, Thilo Kielman...
Hyperspectral imaging is a new technique in remote sensing that generates hundreds of images, corresponding to different wavelength channels, for the same area on the surface of t...
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...
Recent advances in linear classification have shown that for applications such as document classification, the training can be extremely efficient. However, most of the existing t...