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Improving Reproducibility in Machine Learning Research (A Report from the NeurIPS 2019 Reproducibility Program)

, , , , , , , и . (2020)cite arxiv:2003.12206Comment: To appear at JMLR, 16 pages + Appendix.

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Florence Oloff

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Asymptotic performances of a constructive algorithm., и . Neural Processing Letters, 2 (2): 1-4 (1995)Boosting Mixture Models for Semi-supervised Learning., , и . ICANN, том 2130 из Lecture Notes in Computer Science, стр. 41-48. Springer, (2001)Learning Output Embeddings in Structured Prediction., , , , и . CoRR, (2020)Rule Extraction with Fuzzy Neural Network., , и . Int. J. Neural Syst., 5 (1): 1-11 (1994)Anomaly component analysis., , и . CoRR, (2023)Sketch In, Sketch Out: Accelerating both Learning and Inference for Structured Prediction with Kernels., , , и . CoRR, (2023)OKVAR-Boost: a novel boosting algorithm to infer nonlinear dynamics and interactions in gene regulatory networks., , , и . Bioinform., 29 (11): 1416-1423 (2013)Identifying the "right" level of explanation in a given situation., , , , , , , , и . NeHuAI@ECAI, том 2659 из CEUR Workshop Proceedings, стр. 63-66. CEUR-WS.org, (2020)Dynamical Modeling with Kernels for Nonlinear Time Series Prediction., и . NIPS, стр. 129-136. MIT Press, (2003)A Framework to Learn with Interpretation., , и . NeurIPS, стр. 24273-24285. (2021)