activity
20232026
collaborators

8 papers

cs.GT2026

BRAID: Learning Equilibrium Maps in Interdependent Security Games via Weight-Tied Iterative Graph Neural Networks

Elnaz Nowrouzi, Zhiqun Zuo, Xueru Zhang +1

Computing Nash equilibria in interdependent security (IDS) games on networks is computationally expensive: best-response dynamics may need hundreds of iterations per instance, and…

cs.CL2026

TLRD: Teaching LLMs to Reason over Tabular Data with Tri-Level Rationale Distillation

Tianyuan Liang, Xuwei Tan, Lei Shi +6

Tabular data is a primary medium for storing real-world information, driving many industrial applications of machine learning. Traditional predictors achieve strong predictive perf…

cs.LG2026

Individual Fairness In Strategic Classification

Zhiqun Zuo, Mohammad Mahdi Khalili

Strategic classification, where individuals modify their features to influence machine learning (ML) decisions, presents critical fairness challenges. While group fairness in this…

cs.LG2025

Post-processing for Fair Regression via Explainable SVD

Zhiqun Zuo, Ding Zhu, Mohammad Mahdi Khalili

This paper presents a post-processing algorithm for training fair neural network regression models that satisfy statistical parity, utilizing an explainable singular value decompos…

cs.LG2025

An Efficient Training Algorithm for Models with Block-wise Sparsity

Ding Zhu, Zhiqun Zuo, Mohammad Mahdi Khalili

Large-scale machine learning (ML) models are increasingly being used in critical domains like education, lending, recruitment, healthcare, criminal justice, etc. However, the train…

cs.LG2024

Lookahead Counterfactual Fairness

Zhiqun Zuo, Tian Xie, Xuwei Tan +2

As machine learning (ML) algorithms are used in applications that involve humans, concerns have arisen that these algorithms may be biased against certain social groups. \textit{Co…