Bilinear Discriminant Analysis Hashing: A Supervised Hashing Approach for High-Dimensional Data.
Yanzhen LiuXiao BaiCheng YanJun ZhouPublished in: ACCV (5) (2016)
Keyphrases
- discriminant analysis
- high dimensional data
- linear discriminant analysis
- similarity search
- dimensionality reduction
- nearest neighbor
- random projections
- high dimensional
- nearest neighbor search
- hamming space
- dimension reduction
- low dimensional
- hash functions
- binary codes
- high dimensionality
- feature extraction
- subspace clustering
- data distribution
- small sample size
- face recognition
- data sets
- principal component analysis
- data points
- original data
- manifold learning
- unsupervised learning
- fisher discriminant analysis
- dimensionality reduction methods
- null space
- data analysis
- hamming distance
- supervised dimensionality reduction
- high dimensional spaces
- low rank
- principal components analysis
- feature selection
- scatter matrices
- locality sensitive hashing
- input space
- sparse representation
- lower dimensional
- support vector
- semi supervised
- supervised learning
- subspace learning
- graph embedding
- hashing methods
- feature space