超越次模性：带团体公正约束的随机集合选取统一框架（英文版）

英文标题：Beyond Submodularity: A Unified Framework of Randomized Set Selection with Group Fairness Constraints中文摘要：本文提出了一种新型的随机子集选择框架，用于解决机器学习算法中存在的偏见或歧视问题，该框架结合了群体公平和最优化的因素，具有广泛的应用前景和优化效果。英文摘要：Machine learning algorithms play an important role in a variety of importantdecision-making processes, including targeted advertisement displays, home loanapprovals, and criminal behavior predictions. Given the far-reaching impact ofthese algorithms, it is crucial that they operate fairly, free from bias orp