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Finite Sample Prediction and Recovery Bounds for Ordinal Embedding., , and . NIPS, page 2703-2711. (2016)Optimal Exploration is no harder than Thompson Sampling., , and . AISTATS, volume 238 of Proceedings of Machine Learning Research, page 1684-1692. PMLR, (2024)Pessimistic Off-Policy Multi-Objective Optimization., , , , , and . AISTATS, volume 238 of Proceedings of Machine Learning Research, page 2980-2988. PMLR, (2024)A/B Testing and Best-arm Identification for Linear Bandits with Robustness to Non-stationarity., , , , and . AISTATS, volume 238 of Proceedings of Machine Learning Research, page 1585-1593. PMLR, (2024)Best of Three Worlds: Adaptive Experimentation for Digital Marketing in Practice., , , , and . WWW, page 3586-3597. ACM, (2024)Humor in AI: Massive Scale Crowd-Sourced Preferences and Benchmarks for Cartoon Captioning., , , , , , , , , and 2 other author(s). CoRR, (2024)Learning Low-Dimensional Metrics., , and . NIPS, page 4139-4147. (2017)Sequential Experimental Design for Transductive Linear Bandits., , , and . NeurIPS, page 10666-10676. (2019)Optimal Exploration is no harder than Thompson Sampling., , and . CoRR, (2023)Active Learning with Safety Constraints., , , , and . NeurIPS, (2022)