Regularized covariance matrix estimation with high dimensional data for supervised anomaly detection problems.
Daniel NikovskiKiran ByadarhalyPublished in: IJCNN (2016)
Keyphrases
- anomaly detection
- high dimensional data
- covariance matrix
- high dimensionality
- dimensionality reduction
- principal component analysis
- low dimensional
- high dimensional
- intrusion detection
- nearest neighbor
- unsupervised learning
- data points
- covariance matrices
- data sets
- detecting anomalies
- similarity search
- dimension reduction
- manifold learning
- one class support vector machines
- sample size
- lower dimensional
- sparse representation
- supervised learning
- linear discriminant analysis
- data analysis
- principal components analysis
- feature selection
- learning algorithm
- data distribution
- active learning
- evolutionary algorithm
- feature space
- detect anomalies