AI RESEARCH
Contextual Bandits for Resource-Constrained Devices using Probabilistic Learning
arXiv CS.LG
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ArXi:2605.13346v1 Announce Type: new Contextual bandits (CB) are online sequential decision-making problems under partial feedback that underpin many adaptive services. There is a growing demand to deploy CB agents directly on-device, under strict constraints on memory, compute, and energy. However, standard linear CB algorithms are often impractical for resource-constrained devices with their unfavorable scaling in computational and memory costs.