WATCH: Wasserstein Change Point Detection for High-Dimensional Time Series Data.
Kamil FaberRoberto CorizzoBartlomiej SniezynskiMichael BaronNathalie JapkowiczPublished in: IEEE BigData (2021)
Keyphrases
- change point detection
- high dimensional
- change point
- non stationary
- outlier detection
- singular spectrum analysis
- sequential data
- high dimensional time series
- normalized maximum likelihood
- similarity search
- multi dimensional
- dimensionality reduction
- pointwise
- variable selection
- data points
- feature space
- kernel function
- machine learning
- sequential patterns
- feature vectors
- spatio temporal
- feature selection