A unified global convergence analysis of multiplicative update rules for nonnegative matrix factorization.
Norikazu TakahashiJiro KatayamaMasato SekiJun'ichi TakeuchiPublished in: Comput. Optim. Appl. (2018)
Keyphrases
- nonnegative matrix factorization
- update rules
- update rule
- convergence analysis
- negative matrix factorization
- matrix factorization
- data representation
- global convergence
- least squares
- principal component analysis
- spectral clustering
- document clustering
- machine learning
- optimality conditions
- objective function
- approximation methods
- learning rate
- original data