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Shujun Bi
Abstract
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Model selection and estimation in regression with grouped variables
10.1111/j.1467-9868.2005.00532.x · 2006
Structured compressed sensing: from theory to applications
10.1109/tsp.2011.2161982 · 2011
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Flexible latent variable models for multi-task learning
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Robust recovery of signals from a structured union of subspaces
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On the reconstruction of block-sparse signals with an optimal number of measurements
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A fast unified algorithm for solving group-lasso penalize learning problems
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Optimization problems involving group sparsity terms
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Model selection and estimation in high dimensional regression models with group SCAD
10.1016/j.spl.2015.04.017 · 2015
Group sparse optimization via lp,q regularization
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A sparse semismooth newton based proximal majorization-minimization algorithm for nonconvex square-root-loss regression problems
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Zero-norm regularized problems: equivalent surrogates, proximal MM method and statistical error bound
10.1007/s10589-023-00496-x · 2023
Sparse group fused lasso for model segmentation: a hybrid approach
10.1007/s11634-020-00424-5 · 2021
Local optimality for stationary points of group zero-norm regularized problems and equivalent surrogates
10.1080/02331934.2022.2057853 · 2023
Sparse group lasso: consistency and climate applications
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Asymptotic theory of the adaptive sparse group lasso
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Sparse overlapping sets lasso for multitask learning and its application to FMRI analysis
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Classification with the sparse group lassoy
10.1109/tsp.2015.2488586 · 2015
Multivariate sparse group lasso for the multivariate multiple linear regression with an arbitrary group structurey
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Error bounds for compressed sensing algorithms with group sparsity: a unified approachy
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Proximal alternating linearized minimization for nonconvex and nonsmooth problems
10.1007/s10107-013-0701-9 · doi-reference
Kurdyka-Łojasiewicz exponent via inf-projection
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Kurdyka-Łojasiewicz property of zero-norm composite functions
10.1007/s10957-020-01779-7 · doi-reference
Calculus of the exponent of Kurdyka-Łojasiewicz inequality and its applications to linear convergence of first-order methods
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10.1214/12-sts399 · doi-reference
Error bounds for compressed sensing algorithms with group sparsity: a unified approachy
10.1016/j.acha.2015.11.006 · doi-reference
Multivariate sparse group lasso for the multivariate multiple linear regression with an arbitrary group structurey
10.1111/biom.12292 · doi-reference
Classification with the sparse group lassoy
10.1109/tsp.2015.2488586 · doi-reference
Asymptotic theory of the adaptive sparse group lasso
10.1007/s10463-018-0692-7 · doi-reference
Local optimality for stationary points of group zero-norm regularized problems and equivalent surrogates
10.1080/02331934.2022.2057853 · doi-reference
Sparse group fused lasso for model segmentation: a hybrid approach
10.1007/s11634-020-00424-5 · doi-reference
Zero-norm regularized problems: equivalent surrogates, proximal MM method and statistical error bound
10.1007/s10589-023-00496-x · doi-reference
Model selection and estimation in high dimensional regression models with group SCAD
10.1016/j.spl.2015.04.017 · doi-reference
Optimization problems involving group sparsity terms
10.1007/s10107-018-1277-1 · doi-reference
A fast unified algorithm for solving group-lasso penalize learning problems
10.1007/s11222-014-9498-5 · doi-reference
On the reconstruction of block-sparse signals with an optimal number of measurements
10.1109/tsp.2009.2020754 · doi-reference
Robust recovery of signals from a structured union of subspaces
10.1109/tit.2009.2030471 · doi-reference
Flexible latent variable models for multi-task learning
10.1007/s10994-008-5050-1 · doi-reference
Joint covariate selection for grouped classification
10.1007/s11222-008-9111-x · doi-reference
The group lasso for logistic regression
10.1111/j.1467-9868.2007.00627.x · doi-reference
The benefit of group sparsity
10.1214/09-aos778 · doi-reference
Visual classification with multitask joint sparse representation
10.1109/tip.2012.2205006 · doi-reference
Computational methods for sparse solution of linear inverse problems
10.1109/jproc.2010.2044010 · doi-reference
Structured compressed sensing: from theory to applications
10.1109/tsp.2011.2161982 · doi-reference
Model selection and estimation in regression with grouped variables
10.1111/j.1467-9868.2005.00532.x · doi-reference