9 papers
FDE-Gym: The Last Mile of AI Delivery
Dongxu Yang, Hongda Yan, Renxin Wang +23
Existing agent benchmarks typically evaluate agents on well-specified tasks defined by issue reports, specifications, or task tickets. Real-world customer delivery is different: fo…
Beyond Independent Manipulation: Individual Fairness-aware Strategic Classification with Peer Imitation
Xinpeng Lv, Chunyuan Zheng, Yunxin Mao +9
Strategic classification (SC) investigates scenarios where agents manipulate their features to obtain favorable decisions from predictive models. Existing fairness-aware SC approac…
Beyond Rational Illusion: Behaviorally Realistic Strategic Classification
Xinpeng Lv, Yunxin Mao, Renzhe Xu +11
Strategic classification(SC) studies the interaction between decision models and agents who strategically manipulate their features for favorable outcomes. Existing SC frameworks t…
When Tabular Foundation Models Meet Strategic Tabular Data: A Prior Alignment Approach
Xinpeng Lv, Yunxin Mao, Renzhe Xu +13
Tabular foundation models based on pretrained prior-data fitted networks~(PFNs) have shown strong generalization on diverse tabular tasks, but they are typically designed for \emph…
Partial Fairness Awareness: Belief-Guided Strategic Mechanism for Strategic Agents
Xinpeng Lv, Chunyuan Zheng, Yunxin Mao +8
Strategic machine learning investigates scenarios where agents manipulate their features to receive favorable decisions from predictive models. To address fairness concerns intrins…
Revisiting Zeroth-Order Hessian Approximation: A Single-Step Policy Optimization Lens
Junbin Qiu, Zhaowei Hong, Renzhe Xu +1
Accurate Zeroth-Order (ZO) Hessian estimation is a cornerstone of derivative-free methods, essential for tasks such as bilevel optimization, Bayesian inference, and uncertainty qua…
Lower Bias, Higher Welfare: How Creator Competition Reshapes Bias-Variance Tradeoff in Recommendation Platforms?
Kang Wang, Renzhe Xu, Bo Li
Understanding the bias-variance tradeoff in user representation learning is essential for improving recommendation quality in modern content platforms. While well studied in static…
Heterogeneous Data Game: Characterizing the Model Competition Across Multiple Data Sources
Renzhe Xu, Kang Wang, Bo Li
Data heterogeneity across multiple sources is common in real-world machine learning (ML) settings. Although many methods focus on enabling a single model to handle diverse data, re…
The Limits of Interval-Regulated Price Discrimination
Kamesh Munagala, Yiheng Shen, Renzhe Xu
In this paper, we study third-degree price discrimination in a model first presented by Bergemann, Brooks, and Morris [2015]. Since such price discrimination might create market se…