3 papers
cs.LG2026
Target-Weighted Neyman Allocation: Experimental Design for Heterogeneous Treatment Effects under Population Shift
Hoang Dang, Luan Pham, Minh Nguyen
Randomized experiments are often run in one population to guide decisions in another. Allocating by experimental proportions wastes budget on groups that rarely appear in deploymen…
stat.ME2026
Minimum Specification Perturbation: Robustness as Distance-to-Falsification in Causal Inference
Hoang Dang, Luan Pham, Minh Nguyen
Empirical causal claims depend on many analyst decisions, from selecting covariates to choosing estimators. Existing robustness tools summarize how results vary across these choice…
cs.AI2026
Effect-Level Validation for Causal Discovery
Hoang Dang, Luan Pham, Minh Nguyen
Causal discovery is increasingly applied to large-scale telemetry data to estimate the effects of user-facing interventions, yet its reliability for decision-making in feedback-dri…