The power and popularity of kernel methods stem in part from their ability to handle diverse forms of structured inputs, including vectors, graphs and strings. Recently, several m...
Darrin P. Lewis, Tony Jebara, William Stafford Nob...
Distance-based methods in machine learning and pattern recognition have to rely on a metric distance between points in the input space. Instead of specifying a metric a priori, we...
A frequent problem in density level-set estimation is the choice of the right features that give rise to compact and concise representations of the observed data. We present an eï¬...
There is a ever-growing need to add structure in the form of semantic markup to the huge amounts of unstructured text data now available. We present the technique of shallow seman...
Sameer Pradhan, Kadri Hacioglu, Wayne Ward, James ...
In this paper we consider the problem of multi-object categorization. We present an algorithm that combines support vector machines with local features via a new class of Mercer k...
Barbara Caputo, Christian Wallraven, Maria-Elena N...