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A Bandit You Can Trust

, , и . Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization, ACM, (июня 2023)
DOI: 10.1145/3565472.3592955

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More Powerful A/B Testing Using Auxiliary Data and Deep Learning., , , , и . AIED (2), том 13356 из Lecture Notes in Computer Science, стр. 524-527. Springer, (2022)A Bandit You Can Trust., , и . UMAP, стр. 106-115. ACM, (2023)Cyther: a human-playable, self-tuning robotic zither., , и . NIME, стр. 319-324. nime.org, (2017)Classifying Math Knowledge Components via Task-Adaptive Pre-Trained BERT., , , , , , и . AIED (1), том 12748 из Lecture Notes in Computer Science, стр. 408-419. Springer, (2021)Identifying Struggling Students by Comparing Online Tutor Clickstreams., , и . AIED (2), том 12749 из Lecture Notes in Computer Science, стр. 290-295. Springer, (2021)A Novel Algorithm for Aggregating Crowdsourced Opinions., и . EDM, International Educational Data Mining Society, (2021)Effective Evaluation of Online Learning Interventions with Surrogate Measures., , , и . EDM, International Educational Data Mining Society, (2023)Comparing Different Approaches to Generating Mathematics Explanations Using Large Language Models., , , , , , , , и . AIED (Posters/Late Breaking Results/...), том 1831 из Communications in Computer and Information Science, стр. 290-295. Springer, (2023)Deep Learning or Deep Ignorance? Comparing Untrained Recurrent Models in Educational Contexts., , и . AIED (1), том 13355 из Lecture Notes in Computer Science, стр. 281-293. Springer, (2022)MathBERT: A Pre-trained Language Model for General NLP Tasks in Mathematics Education., , , , , и . CoRR, (2021)