AI RESEARCH
StablePCA: Distributionally Robust Learning of Shared Representations from Multi-Source Data
arXiv CS.LG
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ArXi:2505.00940v3 Announce Type: replace When synthesizing multi-source high-dimensional data, a key objective is to extract low-dimensional representations that effectively approximate the original features across different sources. Such representations facilitate the discovery of transferable structures and help mitigate systematic biases such as batch effects. We