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Cheap and Powerful Tests for Supervised Subspaces: Per-Component Inference for PLS

arXiv:2609.36307v1 Announce Type: cross Abstract: Partial Least Squares (PLS) regression extracts a few outcome-aligned directions in a high-dimensional X and is widely used across applied science, but inference on the resulting fit is either expensive, biased and discouraged, or absent. We reduce…

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  1. 2026-09-30 04:00 · arXiv stat.ML
    Cheap and Powerful Tests for Supervised Subspaces: Per-Component Inference for PLS

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