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Large discrete action spaces (LDAS) remain a central challenge in reinforcement learning. Existing solution approaches can handle unstructured LDAS with up to...

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We study off-policy learning (OPL) of contextual bandit policies in large discrete action spaces where existing methods -- most of which rely crucially on...

Developing accurate off-policy estimators is crucial for both evaluating and optimizing for new policies. The main challenge behind the off-policy estimators...

City plans phased rollout by July after pilot improves parking flow | Jan. 16, 2026 11:08