3 papers
stat.ML2025
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.ML2024
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,…
math.ST2024
Meta-Learning with Generalized Ridge Regression: High-dimensional Asymptotics, Optimality and Hyper-covariance Estimation
Yanhao Jin, Krishnakumar Balasubramanian, Debashis Paul
Meta-learning involves training models on a variety of training tasks in a way that enables them to generalize well on new, unseen test tasks. In this work, we consider meta-learni…