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

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

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Boosting Mixture Models for Semi-supervised Learning., , and . ICANN, volume 2130 of Lecture Notes in Computer Science, page 41-48. Springer, (2001)Sketch In, Sketch Out: Accelerating both Learning and Inference for Structured Prediction with Kernels., , , and . CoRR, (2023)Identifying the "right" level of explanation in a given situation., , , , , , , , and . NeHuAI@ECAI, volume 2659 of CEUR Workshop Proceedings, page 63-66. CEUR-WS.org, (2020)OKVAR-Boost: a novel boosting algorithm to infer nonlinear dynamics and interactions in gene regulatory networks., , , and . Bioinform., 29 (11): 1416-1423 (2013)Dynamical Modeling with Kernels for Nonlinear Time Series Prediction., and . NIPS, page 129-136. MIT Press, (2003)A Framework to Learn with Interpretation., , and . NeurIPS, page 24273-24285. (2021)Sketch In, Sketch Out: Accelerating both Learning and Inference for Structured Prediction with Kernels., , , and . AISTATS, volume 238 of Proceedings of Machine Learning Research, page 109-117. PMLR, (2024)Evaluation of Topographic Clustering and Its Kernelization., , and . ECML, volume 2837 of Lecture Notes in Computer Science, page 265-276. Springer, (2003)Gene networks inference using dynamic Bayesian networks., , , , , and . ECCB, page 138-148. (2003)From the Token to the Review: A Hierarchical Multimodal approach to Opinion Mining., , , , and . EMNLP/IJCNLP (1), page 5538-5547. Association for Computational Linguistics, (2019)