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math.ST2026

Asymptotics of resampling without replacement in robust and logistic regression

Pierre C. Bellec, Takuya Koriyama

This paper studies the asymptotics of resampling without replacement in the proportional regime where dimension and sample size are of the same order. For a given dataset $…

math.ST2025

Precise Asymptotics of Bagging Regularized M-estimators

Takuya Koriyama, Pratik Patil, Jin-Hong Du +2

We characterize the squared prediction risk of ensemble estimators obtained through subagging (subsample bootstrap aggregating) regularized M-estimators and construct a consistent…

math.ST2025

Phase transitions for the existence of unregularized M-estimators in single index models

Takuya Koriyama, Pierre C. Bellec

This paper studies phase transitions for the existence of unregularized M-estimators under proportional asymptotics where the sample size and feature dimension grow proport…

math.ST2025

Error estimation and adaptive tuning for unregularized robust M-estimator

Pierre C. Bellec, Takuya Koriyama

We consider unregularized robust M-estimators for linear models under Gaussian design and heavy-tailed noise, in the proportional asymptotics regime where the sample size n and the…

math.ST2024

Existence of solutions to the nonlinear equations characterizing the precise error of M-estimators

Pierre C. Bellec, Takuya Koriyama

Major progress has been made in the previous decade to characterize the asymptotic behavior of regularized M-estimators in high-dimensional regression problems in the proportional…