arXiv Machine Learning June 29, 2026 By Hao Qin, Chicheng Zhang

Taming the Monster Every Context: Complexity Measure and Unified Framework for Offline-Oracle Efficient Contextual Bandits

Read the original on arXiv Machine Learning →

arXiv:2602. 09456v2 Announce Type: replace Abstract: We propose an algorithmic framework, Offline Estimation to Decisions (OE2D), that efficiently reduces contextual bandit learning with general reward function approximation to offline regression.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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