How to Apply Random Projections to Nonnegative Matrix Factorization with Missing Entries?
Farouk YahayaMatthieu PuigtGilles DelmaireGilles RousselPublished in: EUSIPCO (2019)
Keyphrases
- nonnegative matrix factorization
- random projections
- original data
- data matrix
- measurement matrix
- principal component analysis
- document clustering
- matrix factorization
- negative matrix factorization
- dimensionality reduction
- sparse representation
- data representation
- dimension reduction
- low rank
- data sets
- least squares
- random sampling
- image reconstruction
- low rank matrix
- spectral clustering
- missing data
- objective function
- high dimensional data
- low dimensional
- feature space
- computer vision
- semi supervised
- multiscale
- similarity measure
- feature extraction
- information retrieval