Bayesian latent variable models with applications
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Summary
This thesis explores the use of latent variable models in a number of different settings employing Bayesian methods for inference using latent variable model to perform simultaneous clustering and latent structure analysis of multivariate data.
- Type
- dissertation
- Published
- 2013-06-01
- Cited by
- 1
- References
- 145
- Access
- Open access
- OpenAlex
- https://openalex.org/W823895634
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:60070183
Keywords
Latent class model, Latent variable, Local independence, Probabilistic latent semantic analysis, Latent variable model
References
- Approximating the Distribution for Sums of Products of Normal Variables
- Evaluating Subspace Clustering Algorithms
- Social Network Change Detection
- Model‐based clustering for social networks
- Estimation of Finite Mixture Distributions Through Bayesian Sampling
- The Enron Email Dataset Database Schema and Brief Statistical Report
- Variational Bayesian inference for the Latent Position Cluster Model
- Algorithms on Strings, Trees, and Sequences - Computer Science and Computational Biology
- Factor Analysis of Restricted and Repetitive Behaviors in Autism Using the Autism Diagnostic Interview-R
- Scalable Variational Inference for Bayesian Variable Selection in Regression, and Its Accuracy in Genetic Association Studies
- Bayesian parameter estimation via variational methods
- Finite Mixture Models
- Pattern Recognition and Machine Learning
- Bayesian analysis of mixture models with an unknown number of components- an alternative to reversible jump methods
- Mixtures of Factor Analysers. Bayesian Estimation and Inference by Stochastic Simulation
- The Small World Problem
- Finite Mixture Models
- Inferring Parameters and Structure of Latent Variable Models by Variational Bayes
- The EM algorithm for mixtures of factor analyzers
- A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection
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