Matrix Decomposition Algorithm

From GM-RKB
(Redirected from factorization model)
Jump to navigation Jump to search

A Matrix Decomposition Algorithm is a matrix processing algorithm that can be applied by a matrix decomposition system (to solve a matrix decomposition task).



References

2019

   2.5. Decomposing signals in components (matrix factorization problems)
       2.5.1. Principal component analysis (PCA)
           2.5.1.1. Exact PCA and probabilistic interpretation
           2.5.1.2. Incremental PCA
           2.5.1.3. PCA using randomized SVD
           2.5.1.4. Kernel PCA
           2.5.1.5. Sparse principal components analysis (SparsePCA and MiniBatchSparsePCA)
       2.5.2. Truncated singular value decomposition and latent semantic analysis
       2.5.3. Dictionary Learning
           2.5.3.1. Sparse coding with a precomputed dictionary
           2.5.3.2. Generic dictionary learning
           2.5.3.3. Mini-batch dictionary learning
       2.5.4. Factor Analysis
       2.5.5. Independent component analysis (ICA)
       2.5.6. Non-negative matrix factorization (NMF or NNMF)
           2.5.6.1. NMF with the Frobenius norm
           2.5.6.2. NMF with a beta-divergence
       2.5.7. Latent Dirichlet Allocation (LDA)

2016

2008

2003