Multi-task manifold learning for small sample size datasets.
Hideaki IshibashiKazushi HigaTetsuo FurukawaPublished in: CoRR (2021)
Keyphrases
- manifold learning
- multi task
- small sample size
- high dimensional
- dimensionality reduction
- high dimensional data
- high dimensionality
- discriminant embedding
- linear discriminant analysis
- multi task learning
- feature selection
- dimension reduction
- low dimensional
- sample size
- dimensionality reduction methods
- learning tasks
- feature extraction
- microarray data
- face recognition
- semi supervised
- data sets
- metric learning
- learning problems
- transfer learning
- multi class
- principal component analysis
- feature space
- data points
- gaussian processes
- recommender systems
- pattern recognition
- sparse representation
- unsupervised learning
- null space
- similarity measure
- nearest neighbor