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Making interval-based clustering rank-aware.

, , и . EDBT, стр. 437-448. ACM, (2011)

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Learning Feature Weights from Positive Cases., , и . ICCBR, том 7969 из Lecture Notes in Computer Science, стр. 134-148. Springer, (2013)The Responsibility Challenge for Data., , , , , и . SIGMOD Conference, стр. 412-414. ACM, (2019)Diversity in Big Data: A Review., , , и . Big Data, 5 (2): 73-84 (2017)MithraLabel: Flexible Dataset Nutritional Labels for Responsible Data Science., , , , и . CIKM, стр. 2893-2896. ACM, (2019)Taming Technical Bias in Machine Learning Pipelines., и . IEEE Data Eng. Bull., 43 (4): 39-50 (2020)Algorithmic Techniques for Necessary and Possible Winners., , , , , и . Trans. Data Sci., 2 (3): 22:1-22:23 (2021)Transparency, Fairness, Data Protection, Neutrality: Data Management Challenges in the Face of New Regulation., и . ACM J. Data Inf. Qual., 11 (3): 15:1-15:9 (2019)COVID-19 Brings Data Equity Challenges to the Fore., , и . Digit. Gov. Res. Pract., 2 (2): 24:1-24:7 (2021)The Possibility of Fairness: Revisiting the Impossibility Theorem in Practice., , , , , и . CoRR, (2023)Teaching Responsible Data Science.. DataEd@SIGMOD, стр. 4-9. ACM, (2022)