Sequential change-point detection in high-dimensional Gaussian graphical models.
Hossein KeshavarzGeorge MichailidisYves F. AtchadéPublished in: CoRR (2018)
Keyphrases
- change point detection
- gaussian graphical models
- sequential data
- high dimensional
- change point
- graphical models
- non stationary
- singular spectrum analysis
- outlier detection
- linear models
- hidden markov models
- normalized maximum likelihood
- high dimensional time series
- variable selection
- low dimensional
- dimensionality reduction
- high dimensionality
- sequential patterns
- belief propagation
- data points
- pattern mining
- sequence data
- sequential pattern mining
- fixed length
- nearest neighbor
- feature space
- machine learning
- dimension reduction
- multi dimensional
- markov random field
- probabilistic model
- spatio temporal
- bayesian networks
- computer vision