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Bavarian: Betweenness Centrality Approximation with Variance-aware Rademacher Averages.

, , and . ACM Trans. Knowl. Discov. Data, 17 (6): 78:1-78:47 (July 2023)

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Uniform Convergence Bounds for Codec Selection., , and . CoRR, (2018)Dividing Good and Better Items Among Agents with Submodular Valuations., , and . CoRR, (2023)Towards Interactive Data Exploration., , , , , , , , , and 12 other author(s). BIRTE (Revised Selected Papers), volume 337 of Lecture Notes in Business Information Processing, page 177-190. Springer, (2017)Empirical Mechanism Design: Designing Mechanisms from Data., , , and . UAI, volume 115 of Proceedings of Machine Learning Research, page 1094-1104. AUAI Press, (2019)Percentile Criterion Optimization in Offline Reinforcement Learning., , , and . CoRR, (2024)Towards Interactive Curation & Automatic Tuning of ML Pipelines., , , , , , , , and . DEEM@SIGMOD, page 1:1-1:4. ACM, (2018)Learning Equilibria of Simulation-Based Games., , , and . CoRR, (2019)The k-Nearest Representatives Classifier: A Distance-Based Classifier with Strong Generalization Bounds., and . DSAA, page 1-10. IEEE, (2017)Learning Simulation-Based Games from Data., , , and . AAMAS, page 1778-1780. International Foundation for Autonomous Agents and Multiagent Systems, (2019)Sharp uniform convergence bounds through empirical centralization., and . NeurIPS, (2020)