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Filtering participants improves generalization in competitions and benchmarks., , и . ESANN, (2022)AI Competitions and Benchmarks, Practical issues: Proposals, grant money, sponsors, prizes, dissemination, publicity., , , , и . CoRR, (2024)Reinforcement learning for Energies of the future and carbon neutrality: a Challenge Design., , , , , и . CoRR, (2022)Codabench: Flexible, easy-to-use, and reproducible meta-benchmark platform., , , , , , , и . Patterns, 3 (7): 100543 (2022)Methodology for Design and Analysis of Machine Learning Competitions. (Méthodologie pour la conception et l'analyse de compétitions en apprentissage automatique).. University of Paris-Saclay, France, (2023)Generation and evaluation of privacy preserving synthetic health data., , , , , и . Neurocomputing, (2020)Winning solutions and post-challenge analyses of the ChaLearn AutoDL challenge 2019, , , , , , , , , и 15 other автор(ы). IEEE Transactions on Pattern Analysis and Machine Intelligence, (2021)To appear.Privacy Preserving Synthetic Health Data., , , , , и . ESANN, (2019)Assessing privacy and quality of synthetic health data., , , , , и . AIDR, стр. 8:1-8:4. ACM, (2019)Winning Solutions and Post-Challenge Analyses of the ChaLearn AutoDL Challenge 2019., , , , , , , , , и 15 other автор(ы). IEEE Trans. Pattern Anal. Mach. Intell., 43 (9): 3108-3125 (2021)