Approximating Sparsest Cut in Low Rank Graphs via Embeddings from Approximately Low Dimensional Spaces.
Yuval RabaniRakesh VenkatPublished in: APPROX-RANDOM (2017)
Keyphrases
- low rank
- low dimensional spaces
- high dimensional data
- subspace clustering
- dimensionality reduction
- low dimensional
- multi type
- matrix factorization
- high dimensional
- missing data
- singular value decomposition
- latent space
- metric space
- high dimensional spaces
- linear combination
- convex optimization
- semi supervised
- high order
- manifold learning
- machine learning
- high dimensionality
- data objects
- image processing
- graph partitioning
- principal component analysis
- data sets
- small number
- nearest neighbor
- knn
- markov random field
- least squares
- learning algorithm