Poisson EPCA

Name	`PoissonEPCA`
$G(\theta)$	$e^\theta$
$g(\theta)$	$e^\theta$
$\mu$ Space^[1]	positive
$\Theta$ Space	real
Appropriate Data	count, probability

Poisson EPCA minimizes the generalized KL divergence making it well-suited for compressing probability profiles. Poisson EPCA has also been used in reinforcement learning to solve partially observed Markov decision processes (POMDPs) with belief compression (Roy et al., 2005).

Documentation

ExpFamilyPCA.PoissonEPCA — Function

PoissonEPCA(indim::Integer, outdim::Integer; options::Options = Options())

Poisson EPCA.

Arguments

indim::Integer: Dimension of the input space.
outdim::Integer: Dimension of the latent (output) space.
options::Options: Optional parameters.

Returns

epca: An EPCA subtype for the Poisson distribution.

source

1$\mu$ space refers to the space of valid regularization parameters, not to the expectation parameter space.