Low-Rank+Sparse Tensor Compression for Neural Networks.
Cole HawkinsHaichuan YangMeng LiLiangzhen LaiVikas ChandraPublished in: CoRR (2021)
Keyphrases
- low rank
- tensor decomposition
- neural network
- high order
- low rank matrix
- trace norm
- rank minimization
- low rank subspace
- low rank matrices
- frobenius norm
- nuclear norm
- matrix factorization
- robust principal component analysis
- missing data
- convex optimization
- low rank representation
- linear combination
- matrix completion
- matrix decomposition
- singular value decomposition
- kernel matrices
- low rank approximation
- tensor factorization
- high dimensional data
- image compression
- pattern recognition
- minimization problems
- semi supervised
- data representation
- kernel matrix
- higher order
- regularized regression
- auxiliary information
- compressive sensing
- sparse matrix
- dimensionality reduction
- high dimensional
- machine learning
- small number
- low rank and sparse
- data sets