Shypd.aiThe largest open index of AI toolsml-systems-papers is a curated collection of papers in machine learning systems, covering topics like data processing, distributed storage, and ML training. It helps researchers and engineers stay informed about advancements in ML systems.
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ml-systems-papers is a comprehensive, curated collection of academic papers focused on machine learning systems. This GitHub repository serves as a valuable resource for researchers and engineers, offering organized lists of papers across various critical domains. Key topics include data processing optimization, caching and distributed storage for ML training, LLM data planes, and advanced training systems like resource scheduling and AutoML. The collection also delves into inference systems, GPU memory management, compiler optimizations, and federated learning. Survey papers are clearly annotated, making it easier to identify foundational overviews within specific areas of ML systems.
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