We propose a unified data modeling approach that is equally applicable to supervised regression and classification applications, as well as to unsupervised probability density func...
A novel technique is presented to construct sparse regression models based on the orthogonal least square method with boosting. This technique tunes the mean vector and diagonal c...
An m-sample semiparametric model in which the ratio of m - 1 probability density functions with respect to the mth is of a known parametric form without reference to any parametri...