Low-rank Embedding of Kernels in Convolutional Neural Networks under Random Shuffling.
Chao LiZhun SunJinshi YuMing HouQibin ZhaoPublished in: ICASSP (2019)
Keyphrases
- low rank
- convolutional neural networks
- linear combination
- kernel matrices
- convex optimization
- missing data
- matrix factorization
- kernel matrix
- matrix completion
- singular value decomposition
- low rank matrix
- positive semidefinite
- rank minimization
- semi supervised
- trace norm
- high order
- kernel learning
- high dimensional data
- robust principal component analysis
- singular values
- minimization problems
- matrix decomposition
- low rank matrices
- multiple kernel learning
- vector space
- collaborative filtering
- kernel methods
- missing values
- generative model
- super resolution
- distance measure
- least squares
- optical flow
- support vector