Stochastic Dimensionality Reduction for K-means Clustering
Christos BoutsidisAnastasios ZouziasMichael W. MahoneyPetros DrineasPublished in: CoRR (2011)
Keyphrases
- dimensionality reduction
- data representation
- feature extraction
- high dimensional data
- high dimensional
- principal component analysis
- low dimensional
- feature selection
- structure preserving
- manifold learning
- pattern recognition and machine learning
- principal components
- linear discriminant analysis
- clustering algorithm
- k means
- pattern recognition
- monte carlo
- data sets
- random projections
- nonlinear dimensionality reduction
- input space
- stochastic optimization
- metric learning
- feature space
- data points
- lower dimensional
- high dimensionality
- dimension reduction
- pattern classification
- dimensionality reduction methods
- stochastic process
- face recognition
- stochastic programming
- singular value decomposition
- stochastic nature
- linear projection