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Bilmes, J.A. (1998) A Gentle Tutorial of the EM Algorithm and Its Application to Parameter Estimation for Gaussian Mixture and Hidden Markov Models. Technical Report, University of Berkeley, ICSI-TR-97-021.
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has been cited by the following article:

• TITLE: Machine Learning: An Overview (Part Two)

  AUTHORS: Mohd Izhan Mohd Yusoff

  KEYWORDS: Nonintrusive Load Monitoring (NILM), Combinatorics, Observation Matrix, Pentagon

  JOURNAL NAME: Open Journal of Modelling and Simulation, Vol.14 No.2, April 24, 2026

  ABSTRACT: NILM (Nonintrusive Load Monitoring) or appliance recognition software that uses algorithms, namely Hidden Markov Model (HMM) and Factorial HMM, to detect changes in electricity values entering a building, thus inferring which appliances are used and their individual energy consumption. In this paper, a “simple” technique is introduced that uses combinatorics on a specially designed observation matrix to detect hidden appliances and their electricity usage by dissecting the building’s total electricity usage.