Multiscale Stochastic Representation in High-Dimensional Data Using Gaussian Processes with Implicit Diffusion Metrics.
Charanraj ThimmisettyArman KhodabakhshnejadNima JabbariFred AminzadehRoger G. GhanemKelly RoseJennifer R. BauerCorinne DisenhofPublished in: DyDESS (2014)
Keyphrases
- high dimensional data
- gaussian processes
- multiscale
- latent space
- nearest neighbor
- gaussian process
- dimensionality reduction
- low dimensional
- high dimensional
- gaussian process regression
- data sets
- subspace clustering
- data points
- data analysis
- missing values
- manifold learning
- high dimensional spaces
- gaussian process models
- multi task
- hyperparameters
- feature selection
- closed form
- regression model
- multi class
- image data
- lower dimensional
- feature extraction
- image segmentation
- image processing