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Monarch: Expressive Structured Matrices for Efficient and Accurate Training., , , , , , , , , and . ICML, volume 162 of Proceedings of Machine Learning Research, page 4690-4721. PMLR, (2022)AI Lessons Learned from Experiments in Insider Threat Detection., , , and . AAAI Spring Symposium: What Went Wrong and Why: Lessons from AI Research and Applications, page 49-55. AAAI, (2006)EPON over Coax (EPoC)., , , and . IEEE Communications Magazine, 50 (9): 88-95 (2012)How to Train Your YouTube Recommender., , and . CoRR, (2023)Masked Autoencoders As The Unified Learners For Pre-Trained Sentence Representation., and . CoRR, (2022)Generative Oversampling for Mining Imbalanced Datasets., , and . DMIN, page 66-72. CSREA Press, (2007)REVISE: A Tool for Measuring and Mitigating Bias in Visual Datasets., , , , , , , , and . Int. J. Comput. Vis., 130 (7): 1790-1810 (2022)Spatially Cost-Sensitive Active Learning., , and . SDM, page 814-825. SIAM, (2009)Transfer Learning for Entity Recognition of Novel Classes., , and . COLING, page 1974-1985. Association for Computational Linguistics, (2018)Predicting Success and Failure in Weight Loss Blogs through Natural Language Use., , , and . ICWSM, The AAAI Press, (2008)