On Clustering and Embedding Manifolds using a Low Rank Neighborhood Approach.
Arun M. SaranathanMario ParentePublished in: CoRR (2016)
Keyphrases
- low rank
- high dimensional data
- nonlinear dimensionality reduction
- matrix factorization
- manifold structure
- convex optimization
- missing data
- low rank matrix
- linear combination
- matrix completion
- rank minimization
- clustering algorithm
- low dimensional
- manifold learning
- high order
- singular value decomposition
- k means
- semi supervised
- multidimensional scaling
- matrix decomposition
- affinity matrix
- clustering method
- trace norm
- latent space
- high dimensional
- singular values
- missing values
- data points
- kernel matrix
- dimensionality reduction
- feature selection
- data matrix
- low rank matrices
- data analysis
- document clustering
- least squares
- minimization problems
- data clustering
- robust principal component analysis
- subspace clustering
- data sets
- higher order
- nearest neighbor
- machine learning
- nonnegative matrix factorization
- euclidean space
- cluster analysis
- pattern recognition