StablePCA: Distributionally Robust Learning of Shared Representations from Multi-Source Data

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 biase