Compressed Randomized Utv Decompositions for Low-rank Matrix Approximations in Data Science.
Maboud F. KalooraziRodrigo C. de LamarePublished in: ICASSP (2019)
Keyphrases
- low rank matrix
- data science
- singular value decomposition
- matrix approximation
- approximation methods
- low rank
- matrix decomposition
- big data
- statistical learning
- machine learning
- matrix factorization
- convex optimization
- least squares
- dimension reduction
- data matrix
- missing data
- data processing
- sparse matrix
- principal component analysis
- high dimensional data
- belief state
- singular values
- low rank approximation
- semi supervised
- high order
- dimensionality reduction
- data warehouse