Inference and Verification of Probabilistic Graphical Models from High-Dimensional Data.
Yinjiao MaKevin DamazynJakob KlingerHaijun GongPublished in: DILS (2015)
Keyphrases
- high dimensional data
- probabilistic graphical models
- exact inference
- graphical models
- probabilistic inference
- parameter learning
- low dimensional
- nearest neighbor
- bayesian networks
- dimensionality reduction
- high dimensional
- approximate inference
- markov networks
- belief propagation
- data sets
- first order logic
- belief networks
- data points
- data analysis
- conditional random fields
- similarity search
- structured prediction
- manifold learning
- latent variables
- bayesian inference
- dynamic bayesian networks
- missing values
- random variables
- input data
- pattern recognition
- message passing
- input space
- statistical learning
- belief functions
- machine learning
- hidden variables
- conditional probabilities
- generative model
- maximum likelihood