3 papers
stat.ML2026
Differentially Private Two-Stage Gradient Descent for Instrumental Variable Regression
Haodong Liang, Yanhao Jin, Krishnakumar Balasubramanian +1
We study instrumental variable regression (IVaR) under differential privacy constraints. Classical IVaR methods (like two-stage least squares regression) rely on solving moment equ…
stat.ML2025
Transformers Handle Endogeneity in In-Context Linear Regression
Haodong Liang, Krishnakumar Balasubramanian, Lifeng Lai
We explore the capability of transformers to address endogeneity in in-context linear regression. Our main finding is that transformers inherently possess a mechanism to handle end…
stat.ML2025
In-context Learning for Mixture of Linear Regressions: Existence, Generalization and Training Dynamics
Yanhao Jin, Krishnakumar Balasubramanian, Lifeng Lai
We investigate the in-context learning capabilities of transformers for the -dimensional mixture of linear regression model, providing theoretical insights into their existence,…