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Papers
Unified Minimax Optimization Framework for Propensity Score Estimation in Debiased Recommendation
AAAI 2026
Distributionally Robust Policy Learning under Concept Drifts
ICML 2025
Generalizing Causal Effects from Randomized Controlled Trials to Target Populations across Diverse Environments
ICML 2025
Model-agnostic meta-learners for estimating heterogeneous treatment effects over time
ICLR 2025
Benchmarking Estimators for Natural Experiments: A Novel Dataset and a Doubly Robust Algorithm
NeurIPS 2024
Benchmarking Observational Studies with Experimental Data under Right-Censoring
AISTATS 2024
Causality for Functional Longitudinal Data
CLeaR 2024
Causal Q-Aggregation for CATE Model Selection
AISTATS 2024
Continuous Treatment Effects with Surrogate Outcomes
ICML 2024
Counterfactual Density Estimation using Kernel Stein Discrepancies
ICLR 2024
Debiased Collaborative Filtering with Kernel-Based Causal Balancing
ICLR 2024
Doubly Robust Causal Effect Estimation under Networked Interference via Targeted Learning
ICML 2024
On Doubly Robust Inference for Double Machine Learning in Semiparametric Regression
JMLR 2024
Policy Learning for Localized Interventions from Observational Data
AISTATS 2024
Unified Covariate Adjustment for Causal Inference
NeurIPS 2024
A Robust Test for the Stationarity Assumption in Sequential Decision Making
ICML 2023
Balanced Off-Policy Evaluation for Personalized Pricing
AISTATS 2023
Causal Isotonic Calibration for Heterogeneous Treatment Effects
ICML 2023
Counterfactually Comparing Abstaining Classifiers
NeurIPS 2023
DRCFS: Doubly Robust Causal Feature Selection
ICML 2023
Estimating Average Causal Effects from Patient Trajectories
AAAI 2023
Multiple Robust Learning for Recommendation
AAAI 2023
TDR-CL: Targeted Doubly Robust Collaborative Learning for Debiased Recommendations
ICLR 2023
Doubly Robust Counterfactual Classification
NeurIPS 2022
Estimation and inference on high-dimensional individualized treatment rule in observational data using split-and-pooled de-correlated score
JMLR 2022