Multipartite Ranking-Selection of Low-Dimensional Instances by Supervised Projection to High-Dimensional Space.
Arash ShahriariPublished in: CoRR (2016)
Keyphrases
- low dimensional
- high dimensional
- distance preserving
- high dimensional data
- manifold learning
- higher dimensional
- data points
- dimension reduction
- euclidean space
- input space
- dimensionality reduction
- principal component analysis
- vector space
- lower dimensional
- high dimensional data space
- embedding space
- ranking algorithm
- discriminant projection
- linear subspace
- high dimensional spaces
- high dimensionality
- ranking functions
- parameter space
- learning to rank
- pairwise distances
- feature space
- low dimensional spaces
- low dimensional manifolds
- metric space
- nonlinear dimensionality reduction
- instance selection
- unsupervised learning
- semi supervised
- manifold structure
- high dimension
- subspace learning
- data sets
- feature selection
- machine learning