Factor-analytic inverse regression for high-dimension, small-sample dimensionality reduction.
Aditi JhaMichael J. MoraisJonathan W. PillowPublished in: ICML (2021)
Keyphrases
- small sample
- high dimension
- dimensionality reduction
- high dimensionality
- high dimensional
- feature selection
- sample size
- high dimensional data
- low dimensional
- model selection
- regression model
- feature space
- support vector machine
- feature extraction
- principal component analysis
- pattern recognition
- data points
- support vector
- variable selection
- input space
- nearest neighbor
- unsupervised learning
- dimension reduction
- genetic algorithm ga
- feature selection algorithms
- ls svm
- maximum likelihood