SiRA: Sparse Mixture of Low Rank Adaptation.
Yun ZhuNevan WichersChu-Cheng LinXinyi WangTianlong ChenLei ShuHan LuCanoee LiuLiangchen LuoJindong ChenLei MengPublished in: CoRR (2023)
Keyphrases
- low rank
- low rank matrix
- rank minimization
- low rank matrices
- low rank subspace
- nuclear norm
- sparse linear
- sparsity constraints
- robust principal component analysis
- low rank representation
- linear combination
- missing data
- convex optimization
- matrix factorization
- regularized regression
- kernel matrices
- group sparsity
- low rank approximation
- singular value decomposition
- matrix decomposition
- high dimensional data
- matrix completion
- high order
- semi supervised
- tensor decomposition
- singular values
- kernel matrix
- sparse matrix
- sparse coding
- high dimensional
- minimization problems
- trace norm
- affinity matrix
- foreground detection
- data sets
- binary matrices
- data matrix
- interior point methods
- compressive sensing
- dictionary learning
- pattern recognition