Robust Best Point Selection under Unreliable User Feedback
Summary: Find user's utility via pairwise comparisons under both persistent and random response errors—extending beyond prior work that assumes reliable or only random-noisy answers. Propose two algorithms: one with asymptotically optimal query complexity and another using even fewer queries empirically with provable guarantees; outperforms baselines on real and synthetic datasets. (summarized by gpt-5-mini on Feb 09 2026)
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