AI RESEARCH
Scaling Federated Linear Contextual Bandits via Sketching
arXiv CS.LG
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ArXi:2605.00500v1 Announce Type: new In federated contextual linear bandits, high data dimensionality incurs prohibitive computation and communication costs: local agents perform $O(d^3)$-time determinant computation and upload $O(d^2)$ parameters, making existing algorithms unscalable, where $d$ is the dimension of data. To relieve these scaling bottlenecks, this paper proposes Federated Sketch Contextual Linear Bandits