Decomposable-Net: Scalable Low-Rank Compression for Neural Networks.
Atsushi YaguchiTaiji SuzukiShuhei NittaYukinobu SakataAkiyuki TanizawaPublished in: IJCAI (2021)
Keyphrases
- low rank
- neural network
- missing data
- linear combination
- matrix factorization
- matrix completion
- convex optimization
- singular value decomposition
- low rank matrix
- kernel matrix
- rank minimization
- semi supervised
- matrix decomposition
- high dimensional data
- image compression
- pattern recognition
- high order
- trace norm
- robust principal component analysis
- singular values
- collaborative filtering
- computer vision
- low rank representation
- low rank matrices
- higher order
- convex relaxation
- affinity matrix
- principal component analysis
- minimization problems
- input image
- high dimensional
- non rigid structure from motion
- data mining