An Accelerated Expectation-Maximization Algorithm for Multi-Reference Alignment

An Expectation Maximization Algorithm for Textual Unit Alignment

The paper presents an Expectation Maximization (EM) algorithm for automatic generation of parallel and quasi-parallel data from any degree of comparable corpora ranging from parallel to weakly comparable. Specifically, we address the problem of extracting related textual units (documents, paragraphs or sentences) relying on the hypothesis that, in a given corpus, certain pairs of translation eq...

Word Alignment and the Expectation-Maximization Algorithm

The purpose of this tutorial is to give you an example of how to take a simple discrete probabilistic model and derive the expectation maximization updates for it and then turn them into code. We give some examples and identify the key ideas that make the algorithms work. These are meant to be as intuitive as possible, but for those curious about the underlying mathematics, we also provide some...

Expectation Maximization Deconvolution Algorithm

In this paper, we use a general mathematical and experimental methodology to analyze image deconvolution. The main procedure is to use an example image convolving it with a know Gaussian point spread function and then develop algorithms to recover the image. Observe the deconvolution process by adding Gaussian and Poisson noise at different signal to noise ratios. In addition, we will describe ...

The Expectation Maximization Algorithm

This note represents my attempt at explaining the EM algorithm (Hartley, 1958; Dempster et al., 1977; McLachlan and Krishnan, 1997). This is just a slight variation on TomMinka’s tutorial (Minka, 1998), perhaps a little easier (or perhaps not). It includes a graphical example to provide some intuition. 1 Intuitive Explanation of EM EM is an iterative optimizationmethod to estimate some unknown ...

Expectation-Maximization (EM) algorithm