Linear minimum mean-square error estimation based on high-dimensional data with missing values.
Mahdi ZamanighomiZhengdao WangKonstantinos SlavakisGeorgios B. GiannakisPublished in: CISS (2014)
Keyphrases
- high dimensional data
- missing values
- error estimation
- nearest neighbor
- dimensionality reduction
- high dimensional
- low dimensional
- data sets
- model selection
- incomplete data
- high dimensionality
- data analysis
- data points
- data imputation
- dimension reduction
- similarity search
- subspace clustering
- original data
- low rank
- gene expression data
- clustering high dimensional data
- linear discriminant analysis
- support vector machine
- generalization error
- sparse representation
- input data
- data streams
- principal component analysis
- objective function
- feature extraction
- manifold learning
- computer vision
- training set
- k nearest neighbor
- machine learning
- imputation methods
- missing attribute values
- neural network