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The Conference on Machine Learning and Systems targets research at the intersection of machine learning and systems. The conference aims to elicit new connections amongst these fields, including identifying best practices and design principles for learning systems, as well as developing novel learning methods and theory tailored to practical machine learning workflows. Topics include: Efficient model training, inference, and serving Large language model (LLM) training, fine-tuning, and inference
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