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We study the problem of estimating multiple linear regression equations for the purpose of both prediction and variable selection.
Bounds for normal approximations of student’s t t and the chi-square distributions
D. L. Wallace · 1959
Earlier work this paper cites.
Hierarchical Bayes conjoint analysis: recovery of partworth heterogeneity from reduced experimental designs
P. J. Lenk, W. S. DeSarbo, P. E. Green, and M. R. Young · 1996
Earlier work this paper cites.
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Earlier work this paper cites.
Econometric Analysis of Cross Section and Panel Data
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Earlier work this paper cites.
Analysis of Panel Data
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The Dantzig selector: Statistical estimation when p is much larger than n
E. Candès and T. Tao · 2005
Earlier work this paper cites.
Convex Analysis and Nonlinear Optimization: Theory and Examples
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Earlier work this paper cites.
Stable recovery of sparse overcomplete representations in the presence of noise
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Earlier work this paper cites.
Bounds for Linear Multi-Task Learning
A. Maurer · 2006
Earlier work this paper cites.
The group Lasso for logistic regression
L. Meier, S. van de Geer, and P. Buhlmann · 2006
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Model selection and estimation in regression with grouped variables
M. Yuan and Y. Lin · 2006
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Simultaneous analysis of Lasso and Dantzig selector
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Some theoretical results on the grouped variable Lasso
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A convex optimization approach to modeling consumer heterogeneity in conjoint estimation
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Spam: Sparse additive models
P. Ravikumar, H. Liu, J. Lafferty, and L. Wasserman · 2007
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Nemirovski’s inequalities revisited
L. Dümbgen, S. A. van de Geer, and J. A. Wellner · 2008
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Variable selection in nonparametric additive models. Manuscript
J. Huang, J. L. Horowitz, and F Wei · 2008
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Sparse recovery in large ensembles of kernel machines
V. Koltchinskii and M. Yuan · 2008
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Sup-norm convergence rate and sign concentration property of Lasso and Dantzig estimators
K. Lounici · 2008
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High-dimensional additive modeling. arXiv:0806.4115
L. Meier, S. van de Geer, and P. Buhlmann · 2008
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On the asymptotic properties of the group Lasso estimator for linear models
Y. Nardi and A. Rinaldo · 2008
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Convex multi-task feature learning
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Consistency of the group Lasso and multiple kernel learning
F. Bach · 2008
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Linear algorithms for online multitask classification
G. Cavallanti, N. Cesa-Bianchi, and C. Gentile · 2008
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Aggregation for Gaussian regression
F. Bunea, A. B. Tsybakov, and M. H. Wegkamp
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Sparsity oracle inequalities for the Lasso
F. Bunea, A. B. Tsybakov, and M. H. Wegkamp
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Union support recovery in high-dimensional multivariate regression
G. Obozinski, M. J. Wainwright, and M. I. Jordan · 2008
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High-dimensional generalized linear models and the Lasso
S. A. van de Geer · 2008
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