5 papers
Unified Inference Framework for Single and Multi-Player Performative Prediction: Method and Asymptotic Optimality
Zhixian Zhang, Xiaotian Hou, Linjun Zhang
Performative prediction characterizes environments where predictive models alter the very data distributions they aim to forecast, triggering complex feedback loops. While prior re…
Repro Samples Method for Model-Free Inference in High-Dimensional Binary Classification
Xiaotian Hou, Peng Wang, Minge Xie +1
This paper presents a novel method for statistical inference in high-dimensional binary models with unspecified structure, where we leverage a (potentially misspecified) sparsity-c…
FactTest: Factuality Testing in Large Language Models with Finite-Sample and Distribution-Free Guarantees
Fan Nie, Xiaotian Hou, Shuhang Lin +3
The propensity of Large Language Models (LLMs) to generate hallucinations and non-factual content undermines their reliability in high-stakes domains, where rigorous control over T…
Finite-Sample and Distribution-Free Fair Classification: Optimal Trade-off Between Excess Risk and Fairness, and the Cost of Group-Blindness
Xiaotian Hou, Linjun Zhang
Algorithmic fairness has become a central concern in modern machine learning and AI applications. However, two pressing challenges remain: (1) The fairness guarantees of existing m…
Repro Samples Method for High-dimensional Logistic Model
Xiaotian Hou, Linjun Zhang, Peng Wang +1
This paper presents a novel method to make statistical inferences for both the model support and regression coefficients in a high-dimensional logistic regression model. Our method…