:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Apfel, Nicolas, Liang, Xiaoran
Format:	Preprint
Published:	2021
Subjects:	Methodology Machine Learning
Online Access:	https://arxiv.org/abs/2101.05774
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

The Falsification Adaptive Set in Linear Models with Instrumental Variables that Violate the Exclusion or Conditional Exogeneity Restriction
by: Apfel, Nicolas, et al.
Published: (2022)

An Agglomerative Clustering of Simulation Output Distributions Using Regularized Wasserstein Distance
by: Ghasemloo, Mohammadmahdi, et al.
Published: (2024)

Distributional Instrumental Variable Method
by: Holovchak, Anastasiia, et al.
Published: (2025)

Agglomerative hierarchical clustering for selecting valid instrumental variables
by: Nicolas Apfel, et al.
Published: (2024)

Nonparametric Instrumental Variable Inference with Many Weak Instruments
by: van der Laan, Lars, et al.
Published: (2025)

Demystifying Spectral Feature Learning for Instrumental Variable Regression
by: Meunier, Dimitri, et al.
Published: (2025)

Generalized Encouragement-Based Instrumental Variables for Counterfactual Regression
by: Wu, Anpeng, et al.
Published: (2024)

Learning Treatment Representations for Downstream Instrumental Variable Regression
by: Lin, Shiangyi, et al.
Published: (2025)

Hierarchical and Density-based Causal Clustering
by: Kim, Kwangho, et al.
Published: (2024)

Mining Causality: AI-Assisted Search for Instrumental Variables
by: Han, Sukjin
Published: (2024)

Identifiability of Sparse Causal Effects using Instrumental Variables
by: Pfister, Niklas, et al.
Published: (2022)

Penalized Generative Variable Selection
by: Wang, Tong, et al.
Published: (2024)

Hierarchical Clustering With Confidence
by: Wu, Di, et al.
Published: (2025)

Hierarchical Linkage Clustering Beyond Binary Trees and Ultrametrics
by: Dreveton, Maximilien, et al.
Published: (2025)

Double Machine Learning for Static Panel Data with Instrumental Variables: New Method and Applications
by: Baiardi, Anna, et al.
Published: (2026)

Testability of Instrumental Variables in Additive Nonlinear, Non-Constant Effects Models
by: Guo, Xichen, et al.
Published: (2024)

A Unified Framework for Variable Selection in Model-Based Clustering with Missing Not at Random
by: Ho, Binh H., et al.
Published: (2025)

Linear Models, Variable Selection, Artificial Intelligence
by: Alrawkan, By Riyadh, et al.
Published: (2026)

Automating the Selection of Proxy Variables of Unmeasured Confounders
by: Xie, Feng, et al.
Published: (2024)

Diffusion-Driven High-Dimensional Variable Selection
by: Wang, Minjie, et al.
Published: (2025)

Identification and Debiased Learning of Causal Effects with General Instrumental Variables
by: Chen, Shuyuan, et al.
Published: (2025)

Stability Selection via Variable Decorrelation
by: Nouraie, Mahdi, et al.
Published: (2025)

Double Machine Learning of Continuous Treatment Effects with General Instrumental Variables
by: Chen, Shuyuan, et al.
Published: (2026)

Variable Selection for Comparing High-dimensional Time-Series Data
by: Mitsuzawa, Kensuke, et al.
Published: (2024)

Selective Induction Heads: How Transformers Select Causal Structures In Context
by: D'Angelo, Francesco, et al.
Published: (2025)

A Graphical Approach to State Variable Selection in Off-policy Learning
by: Andersen, Joakim Blach, et al.
Published: (2025)

Asymptotic Inference for Multi-Stage Stationary Treatment Policy with Variable Selection
by: Gao, Daiqi, et al.
Published: (2023)

Chiseling: Powerful and Valid Subgroup Selection via Interactive Machine Learning
by: Cheng, Nathan, et al.
Published: (2025)

Forecasting Multivariate Time Series under Predictive Heterogeneity: A Validation-Driven Clustering Framework
by: Ma, Ziling, et al.
Published: (2026)

A Semiparametric Bayesian Method for Instrumental Variable Analysis with Partly Interval-Censored Time-to-Event Outcome
by: Cui, Elvis Han, et al.
Published: (2025)

Ab Initio Nonparametric Variable Selection for Scalable Symbolic Regression with Large $p$
by: Ye, Shengbin, et al.
Published: (2024)

Latent Network Estimation and Variable Selection for Compositional Data via Variational EM
by: Osborne, Nathan, et al.
Published: (2020)

Robust Variable Selection for High-dimensional Regression with Missing Data and Measurement Errors
by: Zhang, Zhenhao, et al.
Published: (2024)

An Experimental Design for Anytime-Valid Causal Inference on Multi-Armed Bandits
by: Liang, Biyonka, et al.
Published: (2023)

Beyond Cross-Validation: Adaptive Parameter Selection for Kernel-Based Gradient Descents
by: Liu, Xiaotong, et al.
Published: (2026)

Robust Variable Selection and Estimation Via Adaptive Elastic Net S-Estimators for Linear Regression
by: Kepplinger, David
Published: (2021)

The Informed Elastic Net for Fast Grouped Variable Selection and FDR Control in Genomics Research
by: Machkour, Jasin, et al.
Published: (2024)

Robust Ultra-High-Dimensional Variable Selection With Correlated Structure Using Group Testing
by: Guo, Wanru, et al.
Published: (2026)

Sample-Efficient "Clustering and Conquer" Procedures for Parallel Large-Scale Ranking and Selection
by: Zhang, Zishi, et al.
Published: (2024)

Causal Effect Estimation with Learned Instrument Representations
by: Dean, Frances, et al.
Published: (2026)