Why Are Big Data Matrices Approximately Low Rank?
Madeleine UdellAlex TownsendPublished in: SIAM J. Math. Data Sci. (2019)
Keyphrases
- big data
- low rank
- matrix completion
- low rank matrix
- singular value decomposition
- data matrix
- matrix decomposition
- singular values
- frobenius norm
- eigendecomposition
- low rank approximation
- low rank and sparse
- low rank matrices
- data analysis
- matrix factorization
- convex optimization
- missing data
- linear combination
- cloud computing
- affinity matrix
- high dimensional data
- data management
- social media
- rank minimization
- high order
- kernel matrix
- business intelligence
- data processing
- semi supervised
- big data analytics
- trace norm
- data warehousing
- principal component analysis
- knowledge discovery
- rows and columns
- dimensionality reduction
- collaborative filtering
- information retrieval
- database
- real world
- data sets