Statistical signal processing applications usually require the estimation of some parameters
of interest given a set of observed data. These estimates are typically obtained either by …

This is an up-to-date introduction to, and overview of, marginal likelihood computation for
model selection and hypothesis testing. Computing normalizing constants of probability …

The effectiveness of pedagogical approaches to teaching English as a foreign language
(EFL) can be enhanced by ensuring that teachers are in a psychologically sound state …

Abstract Machine learning supports prediction and inference in multivariate and complex
datasets where observations are spatially related to one another. Frequently, these datasets …

The expressive power of Bayesian kernel-based methods has led them to become an
important tool across many different facets of artificial intelligence, and useful to a plethora of …

In this paper we address the problem of performing Bayesian inference for the parameters of
a nonlinear multioutput model and the covariance matrix of the different output signals. We …

Strengthening online learning outcomes requires the establishment of strong student-
teacher relationships to engage students actively in learning activities. Teacher-student …

Purpose: The purpose of this article is to explain standard formulas available for deriving
sample size, the essence of every component of formulas, and available techniques for …

The paper reviews the unilateral and bilateral, one-and two-dimensional Laplace
transforms. The unilateral and bilateral Laplace transforms are compared in the one …

Given the current technological changes, entrepreneurs need to transform their businesses
and become more and more digitalized. The process of digital transformation through digital …