Identifying reducible k-tuples of vectors with subspace-proximity sensitive hashing/filtering.
Gabriella HoldenDaniel ShiuLauren StruttPublished in: CoRR (2023)
Keyphrases
- lower dimensional
- principal components
- input data
- low dimensional
- database
- covariance matrices
- random projections
- basis vectors
- principal component analysis
- vector space
- information filtering
- linear subspace
- subspace learning
- filtering algorithm
- order preserving
- data streams
- feature space
- high dimensional data
- data structure
- hilbert space
- feature extraction
- dot product
- nearest neighbor search
- dimensionality reduction
- kernel based nonlinear
- independent components
- adaptive filtering
- linear combination
- feature vectors
- similarity measure
- database systems
- data sets