A convex relaxation of a dimension reduction problem using the nuclear norm.
Christian LyzellMartin S. AndersenMartin EnqvistPublished in: CDC (2012)
Keyphrases
- dimension reduction
- convex relaxation
- matrix completion
- convex optimization
- globally optimal
- multistage
- multi label
- norm minimization
- feature extraction
- principal component analysis
- low rank
- singular value decomposition
- high dimensional
- optimization methods
- high dimensional data
- multiple kernel learning
- low rank matrix
- dimensionality reduction
- random projections
- low dimensional
- unsupervised learning
- feature selection
- feature space
- cluster analysis
- high dimensionality
- data sets
- graph cuts
- light field
- nearest neighbor
- feature vectors
- total variation
- training data
- input data
- learning algorithm
- singular values
- machine learning
- data mining
- text categorization