The EM Algorithm applied to determining new limit points of Mahler measures

In this work, we propose new candidates expected to be limit points of Mahler measures of polynomials. The tool we use for determining these candidates is the Expectation-Maximization algorithm, whose goal is to optimize the likelihood for the given data points, i.e. the known Mahler measures up to degree 44, to be generated by a specific mixture of Gaussians. We will give the mean (which is a candidate to be a new limit point) and the relative amplitude of each component of the more likely gaussian mixture.