Scaling and Scalability: Provable Nonconvex Low-Rank Tensor Estimation from Incomplete Measurements.
Tian TongCong MaAshley Prater-BennetteErin E. TrippYuejie ChiPublished in: J. Mach. Learn. Res. (2022)
Keyphrases
- low rank
- convex optimization
- missing data
- trace norm
- low rank matrices
- high order
- frobenius norm
- robust principal component analysis
- tensor decomposition
- low rank matrix recovery
- linear combination
- matrix factorization
- matrix completion
- kernel matrix
- semi supervised
- low rank matrix
- singular value decomposition
- rank minimization
- regularized regression
- high dimensional data
- matrix decomposition
- missing values
- minimization problems
- low rank and sparse
- higher order
- kullback leibler divergence
- structure from motion
- low rank approximation
- data matrix
- incomplete data
- dimensionality reduction
- tensor factorization
- nuclear norm
- similarity measure
- image restoration
- singular values
- data representation