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Creators/Authors contains: "Yuxin Tang, Zhimin Ding"

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  1. (, Proceedings of Machine Learning Research)
    The relational data model was designed to facilitate large-scale data management and analytics. We consider the problem of how to differentiate computations expressed relationally. We show experimentally that a relational engine running an auto-differentiated relational algorithm can easily scale to very large datasets, and is competitive with state-of-the-art, special-purpose systems for large-scale distributed machine learning. 
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    Accepted Manuscript Full Text Available