Corpus ID: 2174351

On Model Selection Consistency of Lasso

@article{Zhao2006OnMS,
  title={On Model Selection Consistency of Lasso},
  author={P. Zhao and Bin Yu},
  journal={J. Mach. Learn. Res.},
  year={2006},
  volume={7},
  pages={2541-2563}
}
  • P. Zhao, Bin Yu
  • Published 2006
  • Mathematics, Computer Science
  • J. Mach. Learn. Res.
Sparsity or parsimony of statistical models is crucial for their proper interpretations, as in sciences and social sciences. Model selection is a commonly used method to find such models, but usually involves a computationally heavy combinatorial search. Lasso (Tibshirani, 1996) is now being used as a computationally feasible alternative to model selection. Therefore it is important to study Lasso for model selection purposes. In this paper, we prove that a single condition, which we call… Expand
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References

SHOWING 1-10 OF 18 REFERENCES
A NOTE ON THE LASSO AND RELATED PROCEDURES IN MODEL SELECTION
Regression Shrinkage and Selection via the Lasso
On the LASSO and its dual
High-dimensional graphs and variable selection with the Lasso
Boosted Lasso
Stable recovery of sparse overcomplete representations in the presence of noise
Asymptotics for lasso-type estimators
What Are Degrees of Freedom
...
1
2
...