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Cocolasso for high-dimensional error-in-variables regression
Abhirup Datta,
Hui Zou
Statistics (Twin Cities)
Research output
:
Contribution to journal
›
Article
›
peer-review
65
Scopus citations
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Dive into the research topics of 'Cocolasso for high-dimensional error-in-variables regression'. Together they form a unique fingerprint.
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Keyphrases
Missing Data
100%
Measurement Error
100%
Nonconvex
100%
Least Absolute Shrinkage and Selection Operator (LASSO)
100%
High-dimensional Regression
100%
Cross-validation Method
100%
Errors-in-variables Regression
100%
Simulation Study
50%
Corrupted Data
50%
Superior Performance
50%
Convexity
50%
Statist
50%
Noisy Data
50%
Clean Data
50%
Consistent Selection
50%
Estimation Error Bound
50%
Selection Property
50%
Missing Measurements
50%
Data Error
50%
Mathematics
Cross-Validation
100%
Error Variable
100%
Measurement Error
66%
Simulation Study
33%
Asymptotics
33%
Error Bound
33%