Tuning SVM hyperparameters is an important step in achieving a high-performance learning machine. It is usually done by minimizing an estimate of generalization error based on the...
The structure tensor yields an excellent characterization of the local dimensionality and the corresponding orientation for simple neighborhoods, i.e. neighborhoods exhibiting a s...
A new dynamic vector approach for the selection and management of the configuration of a reconfigurable superscalar processor is proposed. This new method improves on previous wor...
Nick A. Mould, Brian F. Veale, Monte P. Tull, John...
This paper addresses the problem of variable ranking for Support Vector Regression. The relevance criteria that we proposed are based on leave-one-out bounds and some variants and...
In the field of computer vision feature matching in high dimensional feature spaces is a commonly used technique for object recognition. One major problem is to find an adequate s...