From Cross-Validation to SURE: Asymptotic Risk of Tuned Regularized Estimators
Fuente:
arXiv
Saved in:
| Main Authors: | Adusumilli, Karun, Kasy, Maximilian, Wilson, Ashia |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Risk and optimal policies in bandit experiments
by: Adusumilli, Karun
Published: (2021)
by: Adusumilli, Karun
Published: (2021)
Optimal Pre-Analysis Plans: Statistical Decisions Subject to Implementability
by: Kasy, Maximilian, et al.
Published: (2022)
by: Kasy, Maximilian, et al.
Published: (2022)
Dynamically Optimal Treatment Allocation
by: Adusumilli, Karun, et al.
Published: (2019)
by: Adusumilli, Karun, et al.
Published: (2019)
You've Got to be Efficient: Ambiguity, Misspecification and Variational Preferences
by: Adusumilli, Karun
Published: (2026)
by: Adusumilli, Karun
Published: (2026)
Continuous time asymptotic representations for adaptive experiments
by: Adusumilli, Karun
Published: (2026)
by: Adusumilli, Karun
Published: (2026)
How to sample and when to stop sampling: The generalized Wald problem and minimax policies
by: Adusumilli, Karun
Published: (2022)
by: Adusumilli, Karun
Published: (2022)
Regularized DeepIV with Model Selection
by: Li, Zihao, et al.
Published: (2024)
by: Li, Zihao, et al.
Published: (2024)
Compound Selection Decisions: An Almost SURE Approach
by: Chen, Jiafeng, et al.
Published: (2025)
by: Chen, Jiafeng, et al.
Published: (2025)
Is completeness necessary? Estimation in nonidentified linear models
by: Babii, Andrii, et al.
Published: (2017)
by: Babii, Andrii, et al.
Published: (2017)
Smaller Confidence Intervals From IPW Estimators via Data-Dependent Coarsening
by: Kalavasis, Alkis, et al.
Published: (2024)
by: Kalavasis, Alkis, et al.
Published: (2024)
On Efficient Estimation of Distributional Treatment Effects under Covariate-Adaptive Randomization
by: Byambadalai, Undral, et al.
Published: (2025)
by: Byambadalai, Undral, et al.
Published: (2025)
Method-of-Moments Inference for GLMs and Doubly Robust Functionals under Proportional Asymptotics
by: Chen, Xingyu, et al.
Published: (2024)
by: Chen, Xingyu, et al.
Published: (2024)
Estimating Distributional Treatment Effects in Randomized Experiments: Machine Learning for Variance Reduction
by: Byambadalai, Undral, et al.
Published: (2024)
by: Byambadalai, Undral, et al.
Published: (2024)
Training and Testing with Multiple Splits: A Central Limit Theorem for Split-Sample Estimators
by: Fava, Bruno
Published: (2025)
by: Fava, Bruno
Published: (2025)
Anytime-Valid Inference for Double/Debiased Machine Learning of Causal Parameters
by: Dalal, Abhinandan, et al.
Published: (2024)
by: Dalal, Abhinandan, et al.
Published: (2024)
Direct Bias-Correction Term Estimation for Average Treatment Effect Estimation
by: Kato, Masahiro
Published: (2025)
by: Kato, Masahiro
Published: (2025)
An Adversarial Approach to Structural Estimation
by: Kaji, Tetsuya, et al.
Published: (2020)
by: Kaji, Tetsuya, et al.
Published: (2020)
Adaptive maximization of social welfare
by: Cesa-Bianchi, Nicolo, et al.
Published: (2023)
by: Cesa-Bianchi, Nicolo, et al.
Published: (2023)
Riesz Regression As Direct Density Ratio Estimation
by: Kato, Masahiro
Published: (2025)
by: Kato, Masahiro
Published: (2025)
It's Hard to Be Normal: The Impact of Noise on Structure-agnostic Estimation
by: Jin, Jikai, et al.
Published: (2025)
by: Jin, Jikai, et al.
Published: (2025)
A Note on Doubly Robust Estimator in Regression Discontinuity Designs
by: Kato, Masahiro
Published: (2024)
by: Kato, Masahiro
Published: (2024)
Debiased Regression for Root-N-Consistent Conditional Mean Estimation
by: Kato, Masahiro
Published: (2024)
by: Kato, Masahiro
Published: (2024)
Gaussian and Bootstrap Approximation for Matching-based Average Treatment Effect Estimators
by: Shi, Zhaoyang, et al.
Published: (2024)
by: Shi, Zhaoyang, et al.
Published: (2024)
Structure-agnostic Optimality of Doubly Robust Learning for Treatment Effect Estimation
by: Jin, Jikai, et al.
Published: (2024)
by: Jin, Jikai, et al.
Published: (2024)
Sharp Structure-Agnostic Lower Bounds for General Linear Functional Estimation
by: Jin, Jikai, et al.
Published: (2025)
by: Jin, Jikai, et al.
Published: (2025)
What Makes Treatment Effects Identifiable? Characterizations and Estimators Beyond Unconfoundedness
by: Cai, Yang, et al.
Published: (2025)
by: Cai, Yang, et al.
Published: (2025)
Designing Persuasive Experiments
by: Adusumilli, Karun, et al.
Published: (2026)
by: Adusumilli, Karun, et al.
Published: (2026)
Modeling Covariate Transition for Efficient Estimation of Longitudinal Treatment Effects in Randomized Experiments
by: Chihara, Naoki, et al.
Published: (2026)
by: Chihara, Naoki, et al.
Published: (2026)
Combining Experimental and Observational Data for Identification and Estimation of Long-Term Causal Effects
by: Ghassami, AmirEmad, et al.
Published: (2022)
by: Ghassami, AmirEmad, et al.
Published: (2022)
Nearest Neighbor Matching as Least Squares Density Ratio Estimation and Riesz Regression
by: Kato, Masahiro
Published: (2025)
by: Kato, Masahiro
Published: (2025)
Bayesian Semiparametric Causal Inference: Targeted Doubly Robust Estimation of Treatment Effects
by: Sert, Gözde, et al.
Published: (2025)
by: Sert, Gözde, et al.
Published: (2025)
Semi-Supervised Treatment Effect Estimation with Unlabeled Covariates for Prediction-Powered Causal Inference
by: Kato, Masahiro
Published: (2025)
by: Kato, Masahiro
Published: (2025)
The Honest Truth About Causal Trees: Accuracy Limits for Heterogeneous Treatment Effect Estimation
by: Cattaneo, Matias D., et al.
Published: (2025)
by: Cattaneo, Matias D., et al.
Published: (2025)
PUATE: Efficient Average Treatment Effect Estimation from Treated (Positive) and Unlabeled Units
by: Kato, Masahiro, et al.
Published: (2025)
by: Kato, Masahiro, et al.
Published: (2025)
ScoreMatchingRiesz: Score Matching for Debiased Machine Learning and Policy Path Estimation
by: Kato, Masahiro
Published: (2025)
by: Kato, Masahiro
Published: (2025)
Bridging the Gap between Empirical Welfare Maximization and Conditional Average Treatment Effect Estimation in Policy Learning
by: Kato, Masahiro
Published: (2025)
by: Kato, Masahiro
Published: (2025)
Selecting Penalty Parameters of High-Dimensional M-Estimators using Bootstrapping after Cross-Validation
by: Chetverikov, Denis, et al.
Published: (2021)
by: Chetverikov, Denis, et al.
Published: (2021)
Stochastic Deep Learning: A Probabilistic Framework for Modeling Uncertainty in Structured Temporal Data
by: Rice, James
Published: (2026)
by: Rice, James
Published: (2026)
The Condition-Number Principle for Prototype Clustering
by: Li, Romano, et al.
Published: (2026)
by: Li, Romano, et al.
Published: (2026)
Decomposition of Spillover Effects Under Misspecification: Pseudo-true Estimands and a Local-Global Extension
by: Park, Yechan, et al.
Published: (2026)
by: Park, Yechan, et al.
Published: (2026)
Similar Items
-
Risk and optimal policies in bandit experiments
by: Adusumilli, Karun
Published: (2021) -
Optimal Pre-Analysis Plans: Statistical Decisions Subject to Implementability
by: Kasy, Maximilian, et al.
Published: (2022) -
Dynamically Optimal Treatment Allocation
by: Adusumilli, Karun, et al.
Published: (2019) -
You've Got to be Efficient: Ambiguity, Misspecification and Variational Preferences
by: Adusumilli, Karun
Published: (2026) -
Continuous time asymptotic representations for adaptive experiments
by: Adusumilli, Karun
Published: (2026)