Low-rank Interaction with Sparse Additive Effects Model for Large Data Frames

Geneviève Robin, Hoi-To Wai, Julie Josse, Olga Klopp, Eric Moulines

Feb-15-2026, 05:07:39 GMT–Neural Information Processing Systems

In this paper, we introduce alowrank interaction and sparse additive effects(LORIS) model which combines matrix regression on a dictionary and low-rank design, to estimate main effects andinteractions simultaneously.

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Neural Information Processing Systems

Feb-15-2026, 05:07:39 GMT

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Low-rank Interaction with Sparse Additive Effects Model for Large Data Frames
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