Gaussian Graphical Model Exploration and Selection in High Dimension Low Sample Size Setting.
Thomas LartigueSimona BottaniStephanie BaronOlivier ColliotStanley DurrlemanStéphanie AllassonnièrePublished in: IEEE Trans. Pattern Anal. Mach. Intell. (2021)
Keyphrases
- high dimension
- graphical models
- sample size
- small sample
- belief propagation
- structure learning
- random variables
- probabilistic model
- bayesian networks
- model selection
- random sampling
- approximate inference
- upper bound
- real valued
- high dimensional
- conditional random fields
- feature space
- input space
- conditional independence
- data sets
- worst case
- feature selection
- support vector machine
- dimensionality reduction
- hyperparameters
- face recognition