Cover Image

Robust Matrix Estimation with Side Information

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Agarwal, Anish, Choi, Jungjun, Yuan, Ming
Format:	Preprint
Published:	2026
Subjects:	Methodology Econometrics Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Doubly Robust Inference in Causal Latent Factor Models
by: Abadie, Alberto, et al.
Published: (2024)

Synthetic Combinations: A Causal Inference Framework for Combinatorial Interventions
by: Agarwal, Abhineet, et al.
Published: (2023)

Inference for Low-rank Models without Estimating the Rank
by: Choi, Jungjun, et al.
Published: (2023)

High Dimensional Factor Analysis with Weak Factors
by: Choi, Jungjun, et al.
Published: (2024)

A Causal Inference Framework for Data Rich Environments
by: Abadie, Alberto, et al.
Published: (2025)

Estimating the Value of Evidence-Based Decision Making
by: Abadie, Alberto, et al.
Published: (2023)

Adaptive Principal Component Regression with Applications to Panel Data
by: Agarwal, Anish, et al.
Published: (2023)

Synthetic Blips: Generalizing Synthetic Controls for Dynamic Treatment Effects
by: Agarwal, Anish, et al.
Published: (2022)

Calibration Strategies for Robust Causal Estimation: Theoretical and Empirical Insights on Propensity Score-Based Estimators
by: Klaassen, Sven, et al.
Published: (2025)

Double Debiased Covariate Shift Adaptation Robust to Density-Ratio Estimation
by: Kato, Masahiro, et al.
Published: (2023)

Incentive-Aware Synthetic Control: Accurate Counterfactual Estimation via Incentivized Exploration
by: Ngo, Daniel, et al.
Published: (2023)

Multiply-Robust Causal Change Attribution
by: Quintas-Martinez, Victor, et al.
Published: (2024)

Estimating Dyadic Treatment Effects with Unknown Confounders
by: Hoshino, Tadao, et al.
Published: (2024)

Estimating Wage Disparities Using Foundation Models
by: Vafa, Keyon, et al.
Published: (2024)

Robust and Agnostic Learning of Conditional Distributional Treatment Effects
by: Kallus, Nathan, et al.
Published: (2022)

Double Robust Bayesian Inference on Average Treatment Effects
by: Breunig, Christoph, et al.
Published: (2022)

Estimation and Inference for Causal Functions with Multiway Clustered Data
by: Liu, Nan, et al.
Published: (2024)

Estimation of Optimal Dynamic Treatment Assignment Rules under Policy Constraints
by: Sakaguchi, Shosei
Published: (2021)

Estimating Causal Effects with Double Machine Learning -- A Method Evaluation
by: Fuhr, Jonathan, et al.
Published: (2024)

Adaptive Estimation and Uniform Confidence Bands for Nonparametric Structural Functions and Elasticities
by: Chen, Xiaohong, et al.
Published: (2021)

Can We Validate Counterfactual Estimations in the Presence of General Network Interference?
by: Shirani, Sadegh, et al.
Published: (2025)

Active Adaptive Experimental Design for Treatment Effect Estimation with Covariate Choices
by: Kato, Masahiro, et al.
Published: (2024)

Estimating Treatment Effects using Multiple Surrogates: The Role of the Surrogate Score and the Surrogate Index
by: Athey, Susan, et al.
Published: (2016)

Estimating Treatment Effects under Algorithmic Interference: A Structured Neural Networks Approach
by: Zhan, Ruohan, et al.
Published: (2024)

A Note on Doubly Robust Estimator in Regression Discontinuity Designs
by: Kato, Masahiro
Published: (2024)

Robust Inference Methods for Latent Group Panel Models under Possible Group Non-Separation
by: Akgun, Oguzhan, et al.
Published: (2025)

xtdml: Double Machine Learning Estimation to Static Panel Data Models with Fixed Effects in R
by: Polselli, Annalivia
Published: (2025)

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

Bayesian Semiparametric Causal Inference: Targeted Doubly Robust Estimation of Treatment Effects
by: Sert, Gözde, et al.
Published: (2025)

Inferential Theory for Pricing Errors with Latent Factors and Firm Characteristics
by: Choi, Jungjun, et al.
Published: (2025)

Spatially Robust Inference with Predicted and Missing at Random Labels
by: Salerno, Stephen, et al.
Published: (2026)

Robustly estimating heterogeneity in factorial data using Rashomon Partitions
by: Venkateswaran, Aparajithan, et al.
Published: (2024)

A Unified Framework for Estimation of High-dimensional Conditional Factor Models
by: Chen, Qihui
Published: (2022)

Improving the Estimation of Lifetime Effects in A/B Testing via Treatment Locality
by: Chen, Shuze, et al.
Published: (2024)

Bias-Reduced Estimation of Finite Mixtures: An Application to Latent Group Structures in Panel Data
by: Langevin, Raphaël
Published: (2026)

A Large-Scale Empirical Comparison of Meta-Learners and Causal Forests for Heterogeneous Treatment Effect Estimation in Marketing Uplift Modeling
by: Singh, Aman
Published: (2026)

Direct Bias-Correction Term Estimation for Average Treatment Effect Estimation
by: Kato, Masahiro
Published: (2025)

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

An Adversarial Approach to Structural Estimation
by: Kaji, Tetsuya, et al.
Published: (2020)

Partial Identification under Missing Data Using Weak Shadow Variables from Pretrained Models
by: Chen, Hongyu, et al.
Published: (2026)