Momentum-inspired Low-Rank Coordinate Descent for Diagonally Constrained SDPs.
Junhyung Lyle KimJose Antonio Lara BenitezMohammad Taha ToghaniCameron R. WolfeZhiwei ZhangAnastasios KyrillidisPublished in: CoRR (2021)
Keyphrases
- low rank
- missing data
- convex optimization
- low rank matrix
- matrix factorization
- linear combination
- matrix completion
- rank minimization
- high dimensional data
- kernel matrix
- singular value decomposition
- semi supervised
- matrix decomposition
- learning rate
- high order
- trace norm
- group sparsity
- kernel learning
- minimization problems
- low rank representation
- low rank matrices
- neural network
- singular values
- pattern recognition
- stochastic gradient descent
- high dimensional
- pairwise
- machine learning
- data sets
- robust principal component analysis