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Sagan

Paper

Catching a Moving Subspace: Low-Rank Bandits Beyond Stationarity

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AI summary

arXiv:2605. 20269v1 Announce Type: new Abstract: Many bandit deployments (recommendation, clinical dosing, ad targeting) share two facts prior work handles only in isolation: rewards live on a low-dimensional latent subspace, and that subspace drifts.