Fast Supervised Hashing with Decision Trees for High-Dimensional Data.
Guosheng LinChunhua ShenQinfeng ShiAnton van den HengelDavid SuterPublished in: CVPR (2014)
Keyphrases
- high dimensional data
- decision trees
- similarity search
- dimensionality reduction
- nearest neighbor
- low dimensional
- high dimensional
- high dimensions
- high dimensionality
- subspace clustering
- data analysis
- data sets
- random projections
- nearest neighbor search
- supervised learning
- feature selection
- data points
- machine learning
- original data
- linear discriminant analysis
- semi supervised
- training set
- hash functions
- input space
- dimension reduction
- dimensional data
- high dimensional spaces
- data distribution
- sparse representation
- binary codes
- manifold learning
- learning algorithm
- feature space
- unsupervised learning
- high dimensional datasets
- subspace learning
- input data
- text data
- clustering high dimensional data
- small sample size
- lower dimensional
- feature extraction
- hamming space
- nonlinear dimensionality reduction
- locality sensitive hashing
- hamming distance
- data structure
- face recognition
- image processing
- real world