9 papers
Beyond Procedure: Substantive Fairness in Conformal Prediction
Pengqi Liu, Zijun Yu, Mouloud Belbahri +3
Conformal prediction (CP) offers distribution-free uncertainty quantification for machine learning models, yet its interplay with fairness in downstream decision-making remains und…
AutoMAS: A Generic Multi-Agent System for Algorithm Self-Adaptation in Wireless Networks
Dingli Yuan, Jingchen Peng, Jie Fan +3
The wireless communication environment has the characteristic of strong dynamics. Conventional wireless networks operate based on the static rules with predefined algorithms, lacki…
Robust distortion risk metrics and portfolio optimization
Peng Liu, Steven Vanduffel, Yi Xia
We establish sharp upper and lower bounds for distortion risk metrics under distributional uncertainty. The uncertainty sets are characterized by four key features of the underlyin…
Lambda Value-at-Risk under ambiguity and risk sharing
Peng Liu, Alexander Schied
In this paper, we investigate the Lambda Value-at-Risk (VaR) under ambiguity, where the ambiguity is represented by a family of probability measures. We establish that for incr…
Risk sharing with Lambda value at risk under heterogeneous beliefs
Peng Liu, Andreas Tsanakas, Yunran Wei
In this paper, we study the risk sharing problem among multiple agents using Lambda Value-at-Risk as their preference functional, under heterogeneous beliefs, where beliefs are rep…
BPO: Revisiting Preference Modeling in Direct Preference Optimization
Lin Sun, Chuang Liu, Peng Liu +3
Direct Preference Optimization (DPO) have emerged as a popular method for aligning Large Language Models (LLMs) with human preferences. While DPO effectively preserves the relative…