4 papers · 1 filter
Noise-Calibrated Inference from Differentially Private Sufficient Statistics in Exponential Families
Amir Asiaee, Samhita Pal
Many differentially private (DP) data release systems either output DP synthetic data and leave analysts to perform inference as usual, which can lead to severe miscalibration, or…
Improving RCT-Based Treatment Effect Estimation Under Covariate Mismatch via Calibrated Alignment
Amir Asiaee, Samhita Pal
Randomized controlled trials (RCTs) are the gold standard for estimating treatment effects, yet they are often underpowered for detecting effect heterogeneity. Large observational…
Causal Discovery with Mixed Latent Confounding via Precision Decomposition
Amir Asiaee, Samhita Pal, James O'quinn +1
We study causal discovery from observational data in linear Gaussian systems affected by \emph{mixed latent confounding}, where some unobserved factors act broadly across many vari…
DAG DECORation: Continuous Optimization for Structure Learning under Hidden Confounding
Samhita Pal, James O'quinn, Kaveh Aryan +3
We study structure learning for linear Gaussian SEMs in the presence of latent confounding. Existing continuous methods excel when errors are independent, while deconfounding-first…