AI RESEARCH
Worst-case low-rank approximations
arXiv CS.AI
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ArXi:2603.11304v1 Announce Type: cross Real-world data in health, economics, and environmental sciences are often collected across heterogeneous domains (such as hospitals, regions, or time periods). In such settings, distributional shifts can make standard PCA unreliable, in that, for example, the leading principal components may explain substantially less variance in unseen domains than in the