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Calibrating nonconvex penalized regression in ultra-high dimension
Lan Wang, Yongdai Kim, Runze Li
Statistics (Twin Cities)
Research output
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Contribution to journal
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Article
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peer-review
121
Scopus citations
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Dive into the research topics of 'Calibrating nonconvex penalized regression in ultra-high dimension'. Together they form a unique fingerprint.
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Mathematics
Penalized Regression
100%
Oracle
77%
Higher Dimensions
67%
High-dimensional
48%
Estimator
44%
Path
40%
Parameter Tuning
36%
Local Minima
31%
Oracle Property
19%
Random Error
17%
High-dimensional Data
17%
Monte Carlo Study
16%
Asymptotic Theory
15%
Sparsity
15%
Penalty
13%
Data analysis
13%
Gaussian distribution
12%
Covariates
12%
Open Problems
11%
Calculate
11%
Unknown
9%
Performance
8%
Estimate
6%
Class
4%
Business & Economics
Estimator
58%
Random Error
20%
Asymptotic Theory
19%
Monte Carlo Study
17%
Covariates
14%
Penalty
13%
Performance
5%
Factors
5%