Multi-task manifold learning for small sample size datasets.
Hideaki IshibashiKazushi HigaTetsuo FurukawaPublished in: Neurocomputing (2022)
Keyphrases
- manifold learning
- multi task
- small sample size
- high dimensional
- high dimensional data
- dimensionality reduction
- high dimensionality
- feature selection
- discriminant embedding
- linear discriminant analysis
- multi task learning
- low dimensional
- dimension reduction
- sample size
- learning tasks
- metric learning
- feature extraction
- gaussian processes
- face recognition
- feature space
- microarray data
- transfer learning
- dimensionality reduction methods
- multi class
- sparse representation
- learning problems
- nearest neighbor
- semi supervised
- model selection
- principal component analysis
- data points
- null space
- neural network
- singular value decomposition
- unsupervised learning
- em algorithm
- probabilistic model
- pattern recognition
- support vector
- machine learning
- data sets