Selection of an optimal estimator typically relies on either supervised training samples (pairs of measurements and their associated true values), or a prior probability model for...
Abstract. A method for measuring the density of data sets that contain an unknown number of clusters of unknown sizes is proposed. This method, called Pareto Density Estimation (PD...
Empirical divergence maximization is an estimation method similar to empirical risk minimization whereby the Kullback-Leibler divergence is maximized over a class of functions tha...
Density estimation for observational data plays an integral role in a broad spectrum of applications, e.g. statistical data analysis and information-theoretic image registration. ...
ROC curves are one of the most widely used displays to evaluate performance of scoring functions. In the paper, we propose a statistical method for directly optimizing the ROC cur...