Yiling Chen, Chara Podimata, Ariel D. Procaccia, Nisarg Shah
TL;DR本文研究机器学习和机制设计交叉领域，提出了一种策略性机制来解决线性回归中数据噪声与数据源的奖励的一致性问题，并且发现了一类广义抗干扰超平面机制，通过和 Ham Sandwich 定理的联合来证明了这些机制的博弈论属性和存在性。
Abstract
This paper is part of an emerging line of work at the intersection of machine learning and mechanism design, which aims to avoid noise in training data by correctly aligning the incentives of data sources. Specif