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...
Abstract--Recently, sparse approximation has become a preferred method for learning large scale kernel machines. This technique attempts to represent the solution with only a subse...
Simple features constructed from order book data for the EURUSD currency pair were used to construct a set of kernels. These kernels were used both individually and simultaneously...
Tristan Fletcher, Zakria Hussain, John Shawe-Taylo...
The classification of normal and malginant colon tissue cells is crucial to the diagnosis of colon cancer in humans. Given the right set of feature vectors, Support Vector Machines...
We propose a method for sequential Bayesian kernel regression. As is the case for the popular Relevance Vector Machine (RVM) [10, 11], the method automatically identifies the num...