Low-rank kernel decomposition for scalable manifold modeling.
Kazuki MiyazakiShuhei TakanoRyo TsunoHideaki IshibashiTetsuo FurukawaPublished in: SCIS/ISIS (2022)
Keyphrases
- low rank
- kernel matrix
- kernel matrices
- manifold structure
- convex optimization
- linear combination
- matrix factorization
- missing data
- matrix completion
- low rank matrix
- rank minimization
- singular value decomposition
- kernel methods
- tensor decomposition
- matrix decomposition
- semi supervised
- trace norm
- feature space
- affinity matrix
- support vector
- singular values
- riemannian manifolds
- high dimensional data
- kernel function
- collaborative filtering
- kernel learning
- high order
- robust principal component analysis