Tensor-based Kernel Machines with Structured Inducing Points for Large and High-Dimensional Data.
Frederiek WeselKim BatselierPublished in: AISTATS (2023)
Keyphrases
- high dimensional data
- kernel machines
- data points
- low dimensional
- high dimensional
- nearest neighbor
- dimensionality reduction
- high dimensionality
- data analysis
- support vector
- similarity search
- dimension reduction
- data sets
- original data
- low rank
- input space
- sparse representation
- data distribution
- high order
- semi supervised
- euclidean distance
- learning problems
- point sets
- unlabeled data
- manifold learning
- semi supervised learning
- distance function
- labeled and unlabeled data
- feature space
- learning machines
- neural network
- random projections
- euclidean space
- machine learning
- training set
- pairwise
- model selection