Sparse regularized low-rank tensor regression with applications in genomic data analysis.
Le Ou-YangXiao-Fei ZhangHong YanPublished in: Pattern Recognit. (2020)
Keyphrases
- low rank
- trace norm
- sparse regression
- data analysis
- high dimensional data
- tensor decomposition
- regularized regression
- high order
- sparsity constraints
- ell norm
- low rank matrix
- matrix completion
- missing data
- matrix factorization
- low rank subspace
- rank minimization
- frobenius norm
- linear combination
- low rank matrices
- sparse linear
- convex optimization
- singular value decomposition
- nuclear norm
- kernel matrix
- matrix decomposition
- high throughput
- robust principal component analysis
- low rank representation
- semi supervised
- data mining
- machine learning
- tensor factorization
- low rank approximation
- kernel matrices
- biological data
- data sets
- group lasso
- higher order
- dimensionality reduction
- norm minimization
- sparse representation
- singular values
- data matrix
- low dimensional
- reproducing kernel hilbert space
- collaborative filtering
- high dimensional
- pattern recognition