Gaussian Graphical Model exploration and selection in high dimension low sample size setting.
Thomas LartigueSimona BottaniStephanie BaronOlivier ColliotStanley DurrlemanStéphanie AllassonnièrePublished in: CoRR (2020)
Keyphrases
- high dimension
- graphical models
- sample size
- small sample
- belief propagation
- probabilistic model
- structure learning
- random variables
- random sampling
- model selection
- real valued
- approximate inference
- feature selection
- conditional random fields
- high dimensional
- upper bound
- input space
- feature space
- conditional independence
- bayesian networks
- worst case
- hyperparameters
- maximum likelihood
- support vector machine
- dimensionality reduction
- probability distribution
- latent variables
- high dimensional data
- expectation maximization
- data sets