Generalized high-dimensional trace regression via nuclear norm regularization
We study the generalized trace regression with a near low-rank regression coefficient matrix, which extends notion of sparsity for regression coefficient vectors. Specifically, given a matrix covariate X, the probability density function of the response Y is f(Y|X)=c(Y)exp(ϕ−1−Yη∗+b(η∗)), where η∗=t...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier Ltd
2019
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| Subjects: | |
| Online Access: | View Fulltext in Publisher |