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» Flexible latent variable models for multi-task learning
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EMNLP
2008
14 years 11 months ago
Latent-Variable Modeling of String Transductions with Finite-State Methods
String-to-string transduction is a central problem in computational linguistics and natural language processing. It occurs in tasks as diverse as name transliteration, spelling co...
Markus Dreyer, Jason Smith, Jason Eisner
ICML
2010
IEEE
14 years 10 months ago
High-Performance Semi-Supervised Learning using Discriminatively Constrained Generative Models
We develop a semi-supervised learning method that constrains the posterior distribution of latent variables under a generative model to satisfy a rich set of feature expectation c...
Gregory Druck, Andrew McCallum
SPEECH
1998
118views more  SPEECH 1998»
14 years 9 months ago
Dimensionality reduction of electropalatographic data using latent variable models
We consider the problem of obtaining a reduced dimension representation of electropalatographic (EPG) data. An unsupervised learning approach based on latent variable modelling is...
Miguel Á. Carreira-Perpiñán, ...
CORR
2012
Springer
184views Education» more  CORR 2012»
13 years 5 months ago
Noisy-OR Models with Latent Confounding
Given a set of experiments in which varying subsets of observed variables are subject to intervention, we consider the problem of identifiability of causal models exhibiting late...
Antti Hyttinen, Frederick Eberhardt, Patrik O. Hoy...
JMLR
2007
137views more  JMLR 2007»
14 years 9 months ago
Building Blocks for Variational Bayesian Learning of Latent Variable Models
We introduce standardised building blocks designed to be used with variational Bayesian learning. The blocks include Gaussian variables, summation, multiplication, nonlinearity, a...
Tapani Raiko, Harri Valpola, Markus Harva, Juha Ka...