Ordinal Embedding: Approximation Algorithms and Dimensionality Reduction.
Mihai BadoiuErik D. DemaineMohammadTaghi HajiaghayiAnastasios SidiropoulosMorteza ZadimoghaddamPublished in: APPROX-RANDOM (2008)
Keyphrases
- approximation algorithms
- dimensionality reduction
- nonlinear dimensionality reduction
- structure preserving
- graph embedding
- np hard
- embedding space
- special case
- multidimensional scaling
- neighborhood preserving
- worst case
- vertex cover
- dimensionality reduction methods
- manifold learning
- low dimensional
- feature selection
- high dimensional
- facility location problem
- set cover
- high dimensional data
- minimum cost
- pattern recognition
- constant factor
- network design problem
- principal component analysis
- feature extraction
- np hardness
- precedence constraints
- primal dual
- data points
- open shop
- kernel pca
- locally linear embedding
- randomized algorithms
- polynomial time approximation
- feature space
- approximation schemes
- disjoint paths
- approximation ratio
- linear programming
- combinatorial auctions