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Performing statistical inference in high-dimension is an outstanding challenge.
Some comments on c p c_{p}
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The Dantzig selector: statistical estimation when p is much larger than n
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Confidence intervals and hypothesis testing for high-dimensional regression
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Statistics for high-dimensional data
P. Bühlmann and S. van de Geer · 2011
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The Noise Sensitivity Phase Transition in Compressed Sensing
D. Donoho, A. Maleki, and A. Montanari · 2011
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The LASSO risk for gaussian matrices
M. Bayati and A. Montanari · 2012
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Residual variance and the signal-to-noise ratio in high-dimensional linear models
L. H. Dicker · 2012
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The estimation of prediction error
B. Efron · 2012
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Scaled sparse linear regression
T. Sun and C.-H. Zhang · 2012
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On asymptotically optimal confidence regions and tests for high-dimensional models
S. Van de Geer, P. Bühlmann, Y. Ritov, and R. Dezeure · 2014
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Confidence intervals for low dimensional parameters in high dimensional linear models
C.-H. Zhang and S. S. Zhang · 2014
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Controlling the false discovery rate via knockoffs
R. F. Barber, E. J. Candès, et al · 2015
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Universality in polytope phase transitions and message passing algorithms
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High-dimensional inference in misspecified linear models
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Confidence intervals for high-dimensional linear regression: Minimax rates and adaptivity
T. T. Cai and Z. Guo · 2015
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Valid post-selection and post-regularization inference: An elementary, general approach
V. Chernozhukov, C. Hansen, and M. Spindler · 2015
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Asymptotically normal and efficient estimation of covariate-adjusted gaussian graphical model
M. Chen, Z. Ren, H. Zhao, and H. Zhou · 2015
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High-dimensional inference: Confidence intervals, p p -values and r-software hdi
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Eigenprism: Inference for high-dimensional signal-to-noise ratios
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Familywise error rate control via knockoffs
L. Janson and W. Su · 2015
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Honest confidence regions and optimality in high-dimensional precision matrix estimation
J. Janková and S. van de Geer · 2015
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Confidence intervals for high-dimensional inverse covariance estimation
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Cross validation in lasso and its acceleration
T. Obuchi and Y. Kabashima · 2015
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Slope is adaptive to unknown sparsity and asymptotically minimax
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Accuracy assessment for high-dimensional linear regression
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