One of the well known risks of large margin training methods, such as boosting and support vector machines (SVMs), is their sensitivity to outliers. These risks are normally mitig...
Multicategory Support Vector Machines (MC-SVM) are powerful classification systems with excellent performance in a variety of biological classification problems. However, the proc...
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...
We propose an improved spoken term detection approach that uses support vector machines trained with lattice context consistency. The basic idea is that the same term usually have...
There are well-established methods for reducing the number of support vectors in a trained binary support vector machine, often with minimal impact on accuracy. We show how reduce...