Scaling and Scalability: Provable Nonconvex Low-Rank Tensor Completion.
Tian TongCong MaAshley Prater-BennetteErin TrippYuejie ChiPublished in: AISTATS (2022)
Keyphrases
- low rank
- convex optimization
- trace norm
- low rank matrices
- frobenius norm
- high order
- robust principal component analysis
- tensor decomposition
- low rank matrix recovery
- singular value decomposition
- matrix factorization
- linear combination
- matrix decomposition
- matrix completion
- low rank matrix
- missing data
- low rank and sparse
- kernel matrix
- semi supervised
- rank minimization
- high dimensional data
- higher order
- pairwise
- primal dual
- singular values
- nuclear norm
- data mining
- minimization problems
- dimensionality reduction
- learning algorithm
- recommender systems
- least squares
- multi task
- tensor factorization
- data matrix
- diffusion tensor