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Probabilistic Distributional Semantics with Latent Variable Models
Distributional Semantics Latent Variable Models
2015/9/14
We describe a probabilistic framework for acquiring selectional preferences of linguistic predicates and for using the acquired representations to model the effects of context on word meaning. Our fra...
Estimation of latent variable models for ordinal data via fully exponential Laplace approximation
GLLVM Bartholomew response pattern parameters latent variable models Laplace
2011/6/17
Latent variable models represent a useful tool in the social sciences where the analyzed
constructs cannot be directly observed and, hence, they are not measurable. However, a set
of indicators rela...
Semiparametric Latent Variable Models for Guided Representation
Variable Models Semiparametric Latent Guided
2011/3/18
Unsupervised discovery of latent representations, in addition to being useful for density modeling, visualisation and exploratory data analysis, is also increasingly important for learning features re...
DE-BIASING WEIGHTED MLE VIA INDIRECT INFERENCE：THE CASE OF GENERALIZED LINEAR LATENT VARIABLE MODELS
factor analysis latent variables M-estimators
2009/2/25
In this paper we study bias-corrections to the weighted MLE (Dupuis and Morgen-
thaler, 2002), a robust estimator simply defined through a weighted score function.
Indeed, although the WMLE is relat...