Sparsity and Geometry Preserving Graph Embedding for Dimensionality Reduction.
Jianping GouZhang YiDavid ZhangYongzhao ZhanXiangjun ShenLan DuPublished in: IEEE Access (2018)
Keyphrases
- graph embedding
- dimensionality reduction
- geometrical structure
- high dimensional
- sparse representation
- low dimensional
- high dimensional data
- data representation
- semi supervised
- pattern recognition
- subspace learning
- principal component analysis
- semi supervised dimensionality reduction
- data points
- discriminant embedding
- unsupervised learning
- manifold learning
- feature space
- embedding space
- euclidean distance
- label information
- feature selection
- feature representation
- dictionary learning
- linear discriminant analysis
- negative matrix factorization
- feature extraction
- geometric structure
- data sets
- metric learning
- sparse coding
- discriminant analysis
- nearest neighbor
- machine learning