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math.ST2023
Universality in block dependent linear models with applications to nonparametric regression
Samriddha Lahiry, Pragya Sur
Over the past decade, characterizing the exact asymptotic risk of regularized estimators in high-dimensional regression has emerged as a popular line of work. This literature consi…
math.ST2023
Spectrum-Aware Debiasing: A Modern Inference Framework with Applications to Principal Components Regression
Yufan Li, Pragya Sur
Debiasing is a fundamental concept in high-dimensional statistics. While degrees-of-freedom adjustment is the state-of-the-art technique in high-dimensional linear regression, it i…