Abstract: Estimation of conditional distributions is considered. It is assumed that the conditional distribution is either discrete or that it has a density with respect to the Lebesgue measure.

Implementation of the Bregman-Correntropy divergence on conditional distributions. Article: Measuring the Discrepancy between Conditional Distributions: Methods ...

In the world of probability theory and statistics, conditional distribution is an essential concept that helps understand the relationship between two or more events. Conditional distribution provides ...

Gaussian Mixture Models are a classic clustering technique, that can easily be generalised to, for example, semi-supervised learning. Sometimes we need to compute closed-form expressions for the ...

This paper is concerned with the computational complexity of learning the Hidden Markov Model (HMM). Although HMMs are some of the most widely used tools in sequential and time series modeling, they ...