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CSDA
2006
94views more  CSDA 2006»
13 years 10 months ago
Simulation-based approach to estimation of latent variable models
We propose a simulation-based method for calculating maximum likelihood estimators in latent variable models. The proposed method integrates a recently developed sampling strategy...
Zhiguang Qian, Alexander Shapiro
JMLR
2006
113views more  JMLR 2006»
13 years 10 months ago
Learning the Structure of Linear Latent Variable Models
We describe anytime search procedures that (1) find disjoint subsets of recorded variables for which the members of each subset are d-separated by a single common unrecorded cause...
Ricardo Silva, Richard Scheines, Clark Glymour, Pe...
CORR
2006
Springer
144views Education» more  CORR 2006»
13 years 10 months ago
Estimation of linear, non-gaussian causal models in the presence of confounding latent variables
The estimation of linear causal models (also known as structural equation models) from data is a well-known problem which has received much attention in the past. Most previous wo...
Patrik O. Hoyer, Shohei Shimizu, Antti J. Kerminen
ACL
2008
13 years 11 months ago
A Discriminative Latent Variable Model for Statistical Machine Translation
Large-scale discriminative machine translation promises to further the state-of-the-art, but has failed to deliver convincing gains over current heuristic frequency count systems....
Phil Blunsom, Trevor Cohn, Miles Osborne
NIPS
2008
13 years 11 months ago
Evaluating probabilities under high-dimensional latent variable models
We present a simple new Monte Carlo algorithm for evaluating probabilities of observations in complex latent variable models, such as Deep Belief Networks. While the method is bas...
Iain Murray, Ruslan Salakhutdinov