Sep 3, 2022 · In this paper, we introduce the em algorithm, an information geometric formulation of the EM algorithm, and its extensions and applications to various problems.

Nov 19, 2022 · In this paper, we introduce the em algorithm, an information geometric formulation of the EM algorithm, and its extensions and applications to various problems.

Nov 19, 2022 · The EM algorithm is a method of performing maximum likelihood estimation by simple iterative computation for problems where a part of the random ...

The Expectation–Maximization (EM) algorithm is a simple meta-algorithm that has been used for many years as a methodology for statistical inference when ...

Nov 12, 2022 · In this paper, we examine a geometrical projection algorithm for statistical inference. The algorithm is based on Pythagorean relation and it is ...

The present paper gives a unified information geometrical framework for studying stochastic models of neural networks, by focusing on the EM and em algorithms.

The "rescaled block-iterative" EMML (RBI-. EMML) is an accelerated block-iterative version of EMML that converges, in the consistent case, to a solution, for ...

The iterative EM reconstruction algorithm is 50 times longer with geometric response and photon attenuation models than without modeling these physical effects.

In statistics, an expectation–maximization (EM) algorithm is an iterative method to find (local) maximum likelihood or maximum a posteriori (MAP) estimates ...

Geometry of EM and related iterative algorithms · Fast Learning of On-line EM Algorithm · The EM Algorithm and Information Geometry in Neural Network Learning.