JMLR

The Matching Principle: When Does a Training Penalty Cover Deployment Shift?

匹配原则：面向干扰鲁棒表示学习的损失函数几何理论

Vishal Rajput

机构 * KU Leuven（根特大学） 纠错

AI总结 提出匹配原则，通过估计任务协方差矩阵并匹配惩罚矩阵的像空间，统一了多种鲁棒性方法，并在线性高斯模型中证明最优性。

Comments 51 pages. Journal-aligned revision of this preprint for JMLR. Title and abstract updated to the even-spread coverage framing. Same author, Matching Principle, and experimental lineage; not a new paper. Under submission at JMLR. Companion: arXiv:2604.21395

From Understanding Genetic Drift to a Smart-Restart Mechanism for Estimation-of-Distribution Algorithms

Weijie Zheng, Benjamin Doerr

Comments Extended version of our GECCO 2020 paper. This article supersedes arXiv:2004.07141

Journal ref Journal of Machine Learning Research 24 (2023) 1-40