This paper presents design and experimental results of a parallel linear equation solver by asynchronous partial Gauss-Seidel method. The basic idea of this method is derived from ...
In recent years manifold methods have attracted a considerable amount of attention in machine learning. However most algorithms in that class may be termed “manifold-motivatedâ€...
In kernel density estimation methods, an approximation of the data probability density function is achieved by locating a kernel function at each data location. The smoothness of ...
: This paper contains description of an knowledge discovery experiment performed in radio planning department of one of Polish celular telecom providers. The results of using vario...
In supervised kernel methods, it has been observed that the performance of the SVM classifier is poor in cases where the diagonal entries of the Gram matrix are large relative to ...