Robust High-Dimensional Linear Discriminant Analysis under Training Data Contamination.
Yuyang ShiAditya DeshmukhYajun MeiVenugopal V. VeeravalliPublished in: ISIT (2023)
Keyphrases
- linear discriminant analysis
- dimensionality reduction
- small sample size
- high dimensional
- training data
- discriminant analysis
- high dimensional data
- dimension reduction
- feature space
- face recognition
- principal component analysis
- feature extraction
- low dimensional
- discriminant features
- support vector machine svm
- sample size
- high dimensionality
- learning algorithm
- support vector
- supervised learning
- data sets
- similarity search
- manifold learning
- classification accuracy
- linear discriminant
- discriminative information
- scatter matrix
- training set
- decision trees
- fisher criterion
- training samples
- feature selection
- null space
- scatter matrices
- qr decomposition
- lower dimensional
- input space
- data points
- support vector machine
- least squares