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

Abstract: Distributionally robust optimization (DRO) is a powerful tool for decision making under uncertainty. It is particularly appealing because of its ability to leverage existing data. However, ...

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.

There was an error while loading. Please reload this page. There are two examples of the conditional Gaussian distribution with Python (Jupyter Notebook) code ...

This is a preview. Log in through your library . Abstract In this paper we present novel results for di screte-ti me and Markovian continuous-time multitype branching processes. As a population ...

As acronyms go, GMM-DCKE – Gaussian mixture model dynamically controlled kernel estimation – is a bit of a mouthful. Its proponents, though, consider it to be the simplest expression of conditional ...

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 ...