4 papers
Personalized Federated Learning via Variance-Aware Nonparametric Empirical Bayes
Jae Ho Chang, Arnab Auddy, Subhadeep Paul
We develop a new approach to Personalized Federated Learning across heterogeneous clients using Nonparametric Empirical Bayes (NPEB). Leveraging the asymptotic normality of local p…
Recidivism Prediction, Peer Effect Estimation, and Prediction-Powered Inference with LLM Text Measures
Shanjukta Nath, Jiwon Hong, Jae Ho Chang +2
We provide a new framework for estimating peer effects when outcomes are multivariate behavioral measures derived from written text using an LLM and the network formation is endoge…
Heterogeneous transfer learning for high-dimensional regression with feature mismatch
Jae Ho Chang, Massimiliano Russo, Subhadeep Paul
We study Heterogeneous Transfer Learning (HTL) for high-dimensional regression with differing feature sets. Such feature mismatch arises when some variables available in a data-ric…
Embedding Network Autoregression for time series analysis and causal peer effect inference
Jae Ho Chang, Subhadeep Paul
We propose an Embedding Network Autoregressive Model for multivariate networked longitudinal data. We assume the network is generated from a latent variable model, and these unobse…