64 search results - page 4 / 13 » Learning Multiple Latent Variables with Self-Organizing Maps |
JMLR
2007
13 years 7 months ago
2007
We introduce standardised building blocks designed to be used with variational Bayesian learning. The blocks include Gaussian variables, summation, multiplication, nonlinearity, a...
EMNLP
2008
13 years 9 months ago
2008
We present a discriminative, latent variable approach to syntactic parsing in which rules exist at multiple scales of refinement. The model is formally a latent variable CRF gramm...
AAAI
2011
12 years 7 months ago
2011
Important ecological phenomena are often observed indirectly. Consequently, probabilistic latent variable models provide an important tool, because they can include explicit model...
ICML
2004
IEEE
14 years 8 months ago
2004
IEEE
We describe a class of causal, discrete latent variable models called Multiple Multiplicative Factor models (MMFs). A data vector is represented in the latent space as a vector of...
ICML
2010
IEEE
13 years 8 months ago
2010
IEEE
Maximum a posteriori (MAP) inference in graphical models requires that we maximize the sum of two terms: a data-dependent term, encoding the conditional likelihood of a certain la...