Model Selection in High-Dimensional Block-Sparse General Linear Regression
Author:
Affiliation:
1. KTH Royal Institute of Technology,Division of Information Science and Engineering, Ericsson,Stockholm,Sweden
2. KTH Royal Institute of Technology,Division of Information Science and Engineering,Stockholm,Sweden
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10289698/10289713/10289738.pdf?arnumber=10289738
Reference39 articles.
1. A practical scheme and fast algorithm to tune the lasso with optimality guarantees;chichignoud;The Journal of Machine Learning Research,2016
2. The Consistency of MDL for Linear Regression Models With Increasing Signal-to-Noise Ratio
3. On the Proper Forms of BIC for Model Order Selection
4. Block sparsity and sampling over a union of subspaces
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