Pith. sign in

REVIEW 1 cited by

EM algorithm and variants: an informal tutorial

Not yet reviewed by Pith; the record is open.

Re-run · record.json Download PDF Read on arXiv ↗

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 1105.1476 v2 pith:VBRO5X7H submitted 2011-05-07 stat.CO

Alexis Roche This is my paper · ORCID
classification stat.CO
keywords algorithminformalvariantsbehindbeyondcurrentdempsterdiscovered
verification ladder T0 review T1 audit T2 compute T3 formal

Signed reviews

No signed human review yet.

0 comments
read the original abstract

The expectation-maximization (EM) algorithm introduced by Dempster et al in 1977 is a very general method to solve maximum likelihood estimation problems. In this informal report, we review the theory behind EM as well as a number of EM variants, suggesting that beyond the current state of the art is an even much wider territory still to be discovered.

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. It's all In the (Exponential) Family: An Equivalence between Maximum Likelihood Estimation and Control Variates for Sketching Algorithms

    stat.ML 2026-01 conditional novelty 6.0 of 10

    In exponential families where the target parameters equal the mean parameters, optimal control variate estimators and maximum likelihood estimators have identical asymptotic variance, giving a fixed-point algorithm fo...

Pith tools