Heterogeneous Recommendation via Deep Low-Rank Sparse Collective Factorization.
Shuhui JiangZhengming DingYun FuPublished in: IEEE Trans. Pattern Anal. Mach. Intell. (2020)
Keyphrases
- low rank
- low rank matrix
- matrix factorization
- low rank subspace
- rank minimization
- low rank matrices
- collaborative filtering
- missing entries
- nuclear norm
- recommender systems
- sparsity constraints
- low rank representation
- robust principal component analysis
- kernel matrices
- convex optimization
- missing data
- group sparsity
- singular value decomposition
- linear combination
- matrix completion
- tensor factorization
- matrix decomposition
- low rank approximation
- regularized regression
- semi supervised
- high order
- kernel matrix
- high dimensional data
- non rigid structure from motion
- tensor decomposition
- factorization methods
- singular values
- data matrix
- trace norm
- low rank and sparse
- latent factors
- high dimensional