Editing Expectation–maximization algorithm (section)

== Further reading ==
* {{cite book |first1=Robert |last1=Hogg |first2=Joseph |last2=McKean |author-link3=Allen Craig |first3=Allen |last3=Craig |title=Introduction to Mathematical Statistics |pages=359–364 |location=Upper Saddle River, NJ |publisher=Pearson Prentice Hall |year=2005 }}
* {{cite report|type=Technical Report number GIT-GVU-02-20|publisher=Georgia Tech College of Computing |url=https://dellaert.github.io/files/em-paper.pdf |title= The Expectation Maximization Algorithm|first=Frank |last= Dellaert |author-link= Frank Dellaert |date=February 2002}} gives an easier explanation of EM algorithm as to lowerbound maximization.
* {{cite book
 |last1 = Bishop |first1 = Christopher M.
 |author-link = Christopher Bishop
 |title = Pattern Recognition and Machine Learning
 |year = 2006
 |publisher = Springer
 |isbn = 978-0-387-31073-2
 }}
* {{cite journal |doi=10.1561/2000000034 |title=Theory and Use of the EM Algorithm |journal=Foundations and Trends in Signal Processing |volume=4 |issue=3 |pages=223–296 |first1=M. R. |last1=Gupta |first2=Y. |last2=Chen |year=2010 |citeseerx=10.1.1.219.6830 }} A well-written short book on EM, including detailed derivation of EM for GMMs, HMMs, and Dirichlet. 
* {{cite report|title= A Gentle Tutorial of the EM Algorithm and its Application to Parameter Estimation for Gaussian Mixture and Hidden Markov Models|first=Jeff |last= Bilmes |year= 1997|type=Technical Report TR-97-021|publisher=International Computer Science Institute|url=https://people.ece.uw.edu/bilmes/p/pgs/b2hd-bilmes1997-em.html}} includes a simplified derivation of the EM equations for Gaussian Mixtures and Gaussian Mixture Hidden Markov Models.
* {{cite book |first1=Geoffrey J. |last1=McLachlan |first2=Thriyambakam |last2=Krishnan |title=The EM Algorithm and Extensions |location=Hoboken |publisher=Wiley |edition=2nd |year=2008 |isbn=978-0-471-20170-0 }}