Gradient Descent with Low-Rank Objective Functions.
Romain CossonAli JadbabaieAnuran MakurAmirhossein ReisizadehDevavrat ShahPublished in: CDC (2023)
Keyphrases
- low rank
- objective function
- cost function
- missing data
- matrix factorization
- convex optimization
- linear combination
- low rank matrix
- matrix completion
- singular value decomposition
- optimal solution
- semi supervised
- high dimensional data
- optimization problems
- rank minimization
- kernel matrix
- matrix decomposition
- high order
- trace norm
- linear programming
- linear program
- singular values
- robust principal component analysis
- low rank matrices
- data analysis
- neural network
- minimization problems
- loss function
- pairwise
- image processing
- non rigid structure from motion
- data sets