Cover Image

Regularized DeepIV with Model Selection

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Li, Zihao, Lan, Hui, Syrgkanis, Vasilis, Wang, Mengdi, Uehara, Masatoshi
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Econometrics Statistics Theory
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Causal Q-Aggregation for CATE Model Selection
by: Lan, Hui, et al.
Published: (2023)

Order-Explicit Linearization of High-Dimensional $U$-Statistics
by: Ritzwoller, David M., et al.
Published: (2024)

Structure-agnostic Optimality of Doubly Robust Learning for Treatment Effect Estimation
by: Jin, Jikai, et al.
Published: (2024)

Sharp Structure-Agnostic Lower Bounds for General Linear Functional Estimation
by: Jin, Jikai, et al.
Published: (2025)

It's Hard to Be Normal: The Impact of Noise on Structure-agnostic Estimation
by: Jin, Jikai, et al.
Published: (2025)

Automatic Doubly Robust Forests
by: Chen, Zhaomeng, et al.
Published: (2024)

Inference on Optimal Policy Values and Other Irregular Functionals via Softmax Smoothing
by: Whitehouse, Justin, et al.
Published: (2025)

Conditional Influence Functions
by: Chernozhukov, Victor, et al.
Published: (2024)

The Partial Testimony of Logs: Evaluation of Language Model Generation under Confounded Model Choice
by: Jin, Jikai, et al.
Published: (2026)

Post Reinforcement Learning Inference
by: Syrgkanis, Vasilis, et al.
Published: (2023)

From Cross-Validation to SURE: Asymptotic Risk of Tuned Regularized Estimators
by: Adusumilli, Karun, et al.
Published: (2026)

Stochastic Deep Learning: A Probabilistic Framework for Modeling Uncertainty in Structured Temporal Data
by: Rice, James
Published: (2026)

Deep Learning for Individual Heterogeneity
by: Farrell, Max H., et al.
Published: (2020)

Dynamic Local Average Treatment Effects
by: Sojitra, Ravi B., et al.
Published: (2024)

Learning Causal Representations from General Environments: Identifiability and Intrinsic Ambiguity
by: Jin, Jikai, et al.
Published: (2023)

Identification and Inference in Nonlinear Dynamic Network Models
by: Vallarino, Diego
Published: (2026)

The Condition-Number Principle for Prototype Clustering
by: Li, Romano, et al.
Published: (2026)

Policy Learning with Abstention
by: Sawarni, Ayush, et al.
Published: (2025)

Adversarial Estimation of Riesz Representers
by: Chernozhukov, Victor, et al.
Published: (2020)

Estimating Distributional Treatment Effects in Randomized Experiments: Machine Learning for Variance Reduction
by: Byambadalai, Undral, et al.
Published: (2024)

Semiparametric inference for impulse response functions using double/debiased machine learning
by: Ballinari, Daniele, et al.
Published: (2024)

Training and Testing with Multiple Splits: A Central Limit Theorem for Split-Sample Estimators
by: Fava, Bruno
Published: (2025)

Ordinary Least Squares as an Attention Mechanism
by: Coulombe, Philippe Goulet
Published: (2025)

Is completeness necessary? Estimation in nonidentified linear models
by: Babii, Andrii, et al.
Published: (2017)

Minimax Semiparametric Learning With Approximate Sparsity
by: Bradic, Jelena, et al.
Published: (2019)

A Heteroskedasticity-Robust Overidentifying Restriction Test with High-Dimensional Covariates
by: Fan, Qingliang, et al.
Published: (2022)

Multiply Robust Causal Mediation Analysis with Continuous Treatments
by: Xu, Yizhen, et al.
Published: (2021)

Nested Nonparametric Instrumental Variable Regression
by: Meza, Isaac, et al.
Published: (2021)

On Efficient Estimation of Distributional Treatment Effects under Covariate-Adaptive Randomization
by: Byambadalai, Undral, et al.
Published: (2025)

Canonical correlation regression with noisy data
by: Meza, Isaac, et al.
Published: (2025)

Learning bounds for doubly-robust covariate shift adaptation
by: Lee, Jeonghwan, et al.
Published: (2025)

Decomposition of Spillover Effects Under Misspecification: Pseudo-true Estimands and a Local-Global Extension
by: Park, Yechan, et al.
Published: (2026)

Empirical Likelihood for Random Forests and Ensembles
by: Chiang, Harold D., et al.
Published: (2025)

Semiparametric Off-Policy Inference for Optimal Policy Values under Possible Non-Uniqueness
by: Wei, Haoyu
Published: (2025)

Functional Sequential Treatment Allocation with Covariates
by: Kock, Anders Bredahl, et al.
Published: (2020)

Kernel methods for long term dose response curves
by: Singh, Rahul, et al.
Published: (2022)

Bayesian Semi-supervised Inference via a Debiased Modeling Approach
by: Sert, Gözde, et al.
Published: (2025)

Modeling Covariate Transition for Efficient Estimation of Longitudinal Treatment Effects in Randomized Experiments
by: Chihara, Naoki, et al.
Published: (2026)

Distance and Kernel-Based Measures for Global and Local Two-Sample Conditional Distribution Testing
by: Yan, Jian, et al.
Published: (2022)

Locally Regular and Efficient Tests in Non-Regular Semiparametric Models
by: Lee, Adam
Published: (2024)