AI RESEARCH
Missing-Data-Induced Phase Transitions in Spectral PLS for Multimodal Learning
arXiv CS.LG
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ArXi:2601.21294v2 Announce Type: replace Partial Least Squares (PLS) learns shared structure from paired data via the top singular vectors of the empirical cross-covariance (PLS-SVD), but multimodal datasets often have missing entries in both views. We study PLS-SVD under independent entry-wise missing-completely-at-random masking in a proportional high-dimensional spiked model.