Laplacian Eigenmaps From Sparse, Noisy Similarity Measurements.
Keith D. LevinVince LyzinskiPublished in: IEEE Trans. Signal Process. (2017)
Keyphrases
- laplacian eigenmaps
- manifold learning
- nonlinear dimensionality reduction
- similarity measure
- high dimensional
- kernel pca
- sparse representation
- empirical mode decomposition
- machine learning
- low dimensional
- euclidean distance
- pattern recognition
- graph laplacian
- dimensionality reduction
- distance measure
- non stationary
- missing data
- sparse coding
- euclidean space
- dynamic time warping