For questions related to the "expectation-maximisation" (EM) algorithm (which is used in several contexts in AI).
For more info, see e.g. https://en.wikipedia.org/wiki/Expectation%E2%80%93maximization_algorithm.
Questions tagged [expectation-maximization]
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What is expectation-maximization in machine learning?
While studying machine learning algorithms, I often see the term "expectation-maximisation" (or EM), and how it is used to estimate parameters, where the model depends on unobserved latent variables.
The way I see it, it is like a…
Guest2000
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Is VAE the same as the E-step of the EM algorithm?
EM(Expectation Maximum)
Target: maximize $p_\theta(x)$
$ p_\theta(x)=\frac{p_\theta(x, z)}{p_\theta(z \mid x)} \\\\$
Take log on both sides:
$ \log p_\theta(x)=\log p_\theta(x, z)-\log p_\theta(z \mid x) \\\\$
Introduce distribution $q_\phi(z)$:
$…
Garfield
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Why is the E step in expectation maximisation algorithm called so?
The E step on the EM algorithm asks us to set the value of the variational lower bound to be equal to the posterior probability of the latent variable, given the data points and parameters. Clearly we are not taking any expectations here, then why…
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Is self-training similar to classification EM helpful?
I am trying to train a model, based on the results of a weak classifier.
Suppose I have some training samples of unlabelled data, and a weak classifier, my procedure is what i call self-training, which means in the first round I train a model with…
