Low-dimensional embedding using adaptively selected ordinal data.
Kevin G. JamiesonRobert D. NowakPublished in: Allerton (2011)
Keyphrases
- ordinal data
- low dimensional
- nonlinear dimensionality reduction
- graph embedding
- embedding space
- multidimensional scaling
- high dimensional
- vector space
- nonlinear manifold learning
- latent space
- manifold learning
- pairwise distances
- high dimensional data
- data points
- principal component analysis
- dimensionality reduction
- low dimensional spaces
- laplacian eigenmaps
- input space
- low dimensional structure
- euclidean space
- dimension reduction
- subspace learning
- linear dimensionality reduction
- feature representation
- linear subspace
- locally linear embedding
- hamming space
- feature space
- lower dimensional
- neural network
- semi supervised
- knn
- image processing