1 citations · 2 across the 7 of their papers we have counts for
7 papers
Inferential Evaluation of Surrogate-Derived Models under Covariate Shift
Longtian Shi, Molei Liu, Doudou Zhou
In transfer-learning settings, a model derived from abundant surrogate labels may be deployed in a target population where gold-standard outcomes are unobserved. Evaluating its tar…
Personalizing Large Language Model Agents with Small Policy Models
Dian Jin, Zhi Zhang, Huichao Li +3
Large language model (LLM) agents can retrieve memory, call tools, ask clarifying questions, and vary response style, yet adapting these execution decisions to an individual user r…
Unlearning What Matters: Token-Level Attribution for Precise Language Model Unlearning
Jiawei Wu, Doudou Zhou
Machine unlearning has emerged as a critical capability for addressing privacy, safety, and regulatory concerns in large language models (LLMs). Existing methods operate at the seq…
RELEAP: Reinforcement-Enhanced Label-Efficient Active Phenotyping for Electronic Health Records
Yang Yang, Kathryn I. Pollak, Bibhas Chakraborty +3
Objective: Electronic health record (EHR) phenotyping often relies on noisy proxy labels, which undermine the reliability of downstream risk prediction. Active learning can reduce…
Toward Fair Federated Learning under Demographic Disparities and Data Imbalance
Qiming Wu, Siqi Li, Doudou Zhou +1
Ensuring fairness is critical when applying artificial intelligence to high-stakes domains such as healthcare, where predictive models trained on imbalanced and demographically ske…
Model-X Change-Point Detection of Conditional Distribution
Zhuofan Dong, Yiwen Huang, Yan Dong +5
The dynamic nature of many real-world systems can lead to temporal outcome model shifts, causing a deterioration in model accuracy and reliability over time. This requires change-p…
SIM-Shapley: A Stable and Computationally Efficient Approach to Shapley Value Approximation
Wangxuan Fan, Siqi Li, Doudou Zhou +4
Explainable artificial intelligence (XAI) is essential for trustworthy machine learning (ML), particularly in high-stakes domains such as healthcare and finance. Shapley value (SV)…