Fast Low-rank Metric Learning for Large-scale and High-dimensional Data.
Han LiuZhizhong HanYu-Shen LiuMing GuPublished in: NeurIPS (2019)
Keyphrases
- high dimensional data
- low rank
- metric learning
- dimensionality reduction
- kernel matrix
- high dimensional
- distance metric
- semi supervised
- nearest neighbor
- low dimensional
- data points
- manifold structure
- similarity search
- subspace clustering
- distance function
- pattern recognition
- feature space
- input space
- data sets
- principal component analysis
- data analysis
- singular value decomposition
- pairwise
- dimension reduction
- manifold learning
- sparse representation
- learning tasks
- unsupervised learning
- subspace learning
- dimensionality reduction methods
- euclidean distance
- feature extraction
- nonlinear dimensionality reduction
- multi task
- original data
- kernel learning
- feature selection
- labeled data
- locally linear embedding
- matrix factorization
- sparse coding
- input data
- distance measure
- active learning