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09/14/2023
Spectrum-Aware Adjustment: A New Debiasing Framework with Applications to Principal Components Regression
We introduce a new debiasing framework for high-dimensional linear regre...
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10/21/2022
A Non-Asymptotic Moreau Envelope Theory for High-Dimensional Generalized Linear Models
We prove a new generalization bound that shows for any class of linear p...
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07/11/2022
Multi-Study Boosting: Theoretical Considerations for Merging vs. Ensembling
Cross-study replicability is a powerful model evaluation criterion that ...
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05/20/2022
A New Central Limit Theorem for the Augmented IPW Estimator: Variance Inflation, Cross-Fit Covariance and Beyond
Estimation of the average treatment effect (ATE) is a central problem in...
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04/09/2022
High-dimensional Asymptotics of Langevin Dynamics in Spiked Matrix Models
We study Langevin dynamics for recovering the planted signal in the spik...
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06/20/2020
Representation via Representations: Domain Generalization via Adversarially Learned Invariant Representations
We investigate the power of censoring techniques, first developed for le...
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04/04/2020
Abstracting Fairness: Oracles, Metrics, and Interpretability
It is well understood that classification algorithms, for example, for d...
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02/05/2020
A Precise High-Dimensional Asymptotic Theory for Boosting and Min-L1-Norm Interpolated Classifiers
This paper establishes a precise high-dimensional asymptotic theory for ...
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01/25/2020
The Asymptotic Distribution of the MLE in High-dimensional Logistic Models: Arbitrary Covariance
We study the distribution of the maximum likelihood estimate (MLE) in hi...
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04/25/2018
The phase transition for the existence of the maximum likelihood estimate in high-dimensional logistic regression
This paper rigorously establishes that the existence of the maximum like...
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03/19/2018
A modern maximum-likelihood theory for high-dimensional logistic regression
Every student in statistics or data science learns early on that when th...
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06/05/2017