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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)

Paper ID
13491
Venue
VLDB
Year
2024
Pagerank
4.1945683e-05
Overall Rank
11,040 | 23.20%
DOI
10.14778/3681954.3681955

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