Abstract. We study high order numerical quadratures to one dimensional delta function integrals in this paper. This is motivated by the fact that traditional numerical quadratures ...
In this paper, we present a wavelet based approach which tries to automatically find the number of clusters present in a data set, along with their position and statistical proper...
We present an algorithm, called the offset tree, for learning in situations where a loss associated with different decisions is not known, but was randomly probed. The algorithm i...
The theory of compressive sampling involves making random linear projections of a signal. Provided signal is sparse in some basis, small number of such measurements preserves the ...
1 Decision Tree Induction is a powerful classification tool that is much used in practice and works well for static data with dozens of attributes. We adapt the decision tree conce...