Generalized multiple change-point detection in the structure of multivariate, possibly high-dimensional, data sequences.
Andreas AnastasiouAngelos PapanastasiouPublished in: Stat. Comput. (2023)
Keyphrases
- high dimensional data
- change point detection
- sequential data
- nearest neighbor
- low dimensional
- dimensionality reduction
- subspace clustering
- high dimensional
- data points
- data sets
- change point
- low dimensional structure
- non stationary
- outlier detection
- dimension reduction
- similarity search
- clustering high dimensional data
- dimensional data
- high dimensionality
- input space
- high dimensional datasets
- manifold learning
- data analysis
- hidden markov models
- underlying manifold
- nonlinear dimensionality reduction
- variable weighting
- computer vision
- variable length
- variable selection
- pattern mining
- multi dimensional
- pattern recognition
- feature extraction