Who Cited It

A gentle tutorial of the em algorithm and its application to parameter estimation for Gaussian mixture and hidden Markov models

1998 · 2,510 citations · 1 from inside this corpus

Jeffrey A. Bilmes

The source holds an abstract for this work, but its best open-access copy is under no open licence, which does not permit us to republish the text. Read it at the source below.

A gentle tutorial of the em algorithm and its application to parameter estimation for Gau… (1998)A gentle tutorial of the em a…The Nature of Statistical Learning Theory (1995)The Nature of Statistical Lea…Statistical Learning Theory (1999)Statistical Learning TheoryNeural networks for pattern recognition (1994)Neural networks for pattern r…Term-weighting approaches in automatic text retrieval (1988)Term-weighting approaches in …Generalized Additive Models. (1991)Generalized Additive Models.Solutions of Ill-Posed Problems. (1978)Solutions of Ill-Posed Proble…Fundamentals of speech recognition (1993)Fundamentals of speech recogn…Pattern Recognition and Neural Networks (1996)Pattern Recognition and Neura…Bayesian Learning for Neural Networks (1996)Bayesian Learning for Neural …A Probabilistic Theory of Pattern Recognition (1996)A Probabilistic Theory of Pat…Mixture Densities, Maximum Likelihood and the EM Algorithm (1984)Mixture Densities, Maximum Li…Hierarchical Mixtures of Experts and the EM Algorithm (1994)Hierarchical Mixtures of Expe…GTM: The Generative Topographic Mapping (1998)GTM: The Generative Topograph…Clustering with Bregman Divergences (2004)Clustering with Bregman Diver…
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What this paper cites, inside the corpus

PaperYearCited
The Nature of Statistical Learning Theory199539,409
Statistical Learning Theory199926,957
Neural networks for pattern recognition199418,720
Term-weighting approaches in automatic text retrieval19889,714
Generalized Additive Models.19918,296
Solutions of Ill-Posed Problems.19788,221
Fundamentals of speech recognition19937,703
Pattern Recognition and Neural Networks19966,514
Bayesian Learning for Neural Networks19964,397
A Probabilistic Theory of Pattern Recognition19963,327
Mixture Densities, Maximum Likelihood and the EM Algorithm19842,720
Hierarchical Mixtures of Experts and the EM Algorithm19942,684
GTM: The Generative Topographic Mapping19981,395

What cites it, inside the corpus

PaperYearCited
Clustering with Bregman Divergences20041,538

Links

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Topics

Bayesian Methods and Mixture ModelsComputer Science
Target Tracking and Data Fusion in Sensor NetworksComputer Science
Blind Source Separation TechniquesComputer Science

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complete

Nothing in this record contradicts itself and no field we check is missing.

  • supports1 author record(s) attached.
  • supports115 reference(s) recorded.
  • neutralThe DOI carries no year to check against.
  • supportsA title is present.

Provenance

Everything above was read from one stored OpenAlex payload, fetched 2026-09-04T03:58:49+00:00.

sha256 a2172c1bbe00c44b…