We present a new approach to estimating mixture models based on a new inference principle we have proposed: the latent maximum entropy principle (LME). LME is different both from ...
Abstract. We present a unified and complete account of maximum entropy distribution estimation subject to constraints represented by convex potential functions or, alternatively, b...
In this work we implement a confidence estimation system based on a Naive Bayes classifier, by using the maximum entropy paradigm. The model takes information from various sourc...
We study the problem of simultaneously estimating several densities where the datasets are organized into overlapping groups, such as a hierarchy. For this problem, we propose a m...
Abstract—In this contribution we present a numerical approach to evaluate the bit error rate and mutual information of OFDM links affected by transmitter nonlinearities, phase no...