6 papers
Learn then Decide: A Learning Approach for Designing Data Marketplaces
Yingqi Gao, Wenlu Xu, Jin J. Zhou +3
As data marketplaces become increasingly central to the digital economy, it is crucial to design efficient pricing mechanisms that optimize revenue while ensuring fair and adaptive…
Prediction-Powered Conditional Inference
Yang Sui, Jin Zhou, Hua Zhou +1
We study prediction-powered conditional inference in the setting where labeled data are scarce, unlabeled covariates are abundant, and a black-box machine-learning predictor is ava…
Uncertainty-Aware Multimodal Learning via Conformal Shapley Intervals
Mathew Chandy, Michael Johnson, Judong Shen +4
Multimodal learning combines information from multiple data modalities to improve predictive performance. However, modalities often contribute unequally and in a data dependent way…
ALIGN: Aligned Delegation with Performance Guarantees for Multi-Agent LLM Reasoning
Tong Zhu, Baiting Chen, Jin Zhou +3
LLMs often underperform on complex reasoning tasks when relying on a single generation-and-selection pipeline. Inference-time ensemble methods can improve performance by sampling d…
Two-Stage Least Squares Instrumental Variable Estimation for Semiparametric Accelerated Failure Time Models with Right-Censored Data
Zian Zhuang, Hua Zhou, Jin Zhou +1
Instrumental variable (IV) analysis is widely used in fields such as economics and epidemiology to address unobserved confounding and measurement error when estimating the causal e…
A Semiparametric Bayesian Method for Instrumental Variable Analysis with Partly Interval-Censored Time-to-Event Outcome
Elvis Han Cui, Xuyang Lu, Jin Zhou +2
This paper develops a semiparametric Bayesian instrumental variable analysis method for estimating the causal effect of an endogenous variable when dealing with unobserved confound…