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Expectation–maximization algorithm

Known as: Expectation Maximization, EM clustering, Expectation maximization method 
In statistics, an expectation–maximization (EM) algorithm is an iterative method for finding maximum likelihood or maximum a posteriori (MAP… 
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Related topics

Related topics

41 relations
Bayesian networkBitext word alignmentCluster analysisComputational anatomy

Broader (2)

Estimation theoryMissing data

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2010
Highly Cited
2010
Stability analysis for cognitive radio with multi-access primary transmission
This letter analyzes the impact, from a network-layer perspective, of having a single cognitive radio transmitter-receiver pair… 
Highly Cited
2003
Highly Cited
2003
Unsupervised Mining of Statistical Temporal Structures in Video
In this chapter we present algorithms for unsupervised mining of struc-tures in video using multi-scale statistical models. Video… 
2003
2003
Blind Source Separation USing Variational Expectation-Maximization Algorithm
In this paper we suggest a new variational Bayesian approach. Variational Expectation-Maximization (VEM) algorithm is proposed in… 
2003
2003
Extensions to the Probabilistic Multi-Hypothesis Tracker for Improved Data Association
Multitarget tracking is a state space estimation problem where false measurements, missed detections, and uncertainty in the… 
Highly Cited
2001
Highly Cited
2001
The Hand Mouse: GMM hand-color classification and mean shift tracking
This paper describes an algorithm to detect and track a hand in each image taken by a wearable camera. We primarily use color… 
Highly Cited
2000
Highly Cited
2000
Markov chain Monte Carlo data association for target tracking
We consider the estimation of the state of a discrete-time Markov process using observations which are sets of measurements from… 
Highly Cited
2000
Highly Cited
2000
Border-Block Triangular Form and Conjunction Schedule in Image Computation
Conjunction scheduling in image computation consists of clustering the parts of a transition relation and ordering the clusters… 
Highly Cited
1998
Highly Cited
1998
Maximizing sets and fuzzy Markoff algorithms
  • L. Zadeh
  • IEEE Trans. Syst. Man Cybern. Part C
  • 1998
  • Corpus ID: 9314136
A fuzzy algorithm is an ordered set of fuzzy instructions that upon execution yield an approximate solution to a given problem… 
Highly Cited
1992
Highly Cited
1992
Electron microscopy at 1-Å resolution by entropy maximization and likelihood ranking
The resolution of electron microscopy may be extended by combining the phase information in microscope images with electron… 
Highly Cited
1982
Highly Cited
1982
The application of decision theory to contingency selection
This paper presents the theory and method for systematically finding the performance index (PI) which is used in Automatic… 
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