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Matrix Computations and Optimization in Apache Spark., , , , , , , , and . KDD, page 31-38. ACM, (2016)Random projection design for scalable implicit smoothing of randomly observed stochastic processes., , , and . AISTATS, volume 54 of Proceedings of Machine Learning Research, page 700-708. PMLR, (2017)Embarrassingly Parallel Time Series Analysis for Large Scale Weak Memory Systems., , , and . CoRR, (2015)KeystoneML: Optimizing Pipelines for Large-Scale Advanced Analytics., , , , and . CoRR, (2016)Scalable Linear Causal Inference for Irregularly Sampled Time Series with Long Range Dependencies., , , , and . CoRR, (2016)linalg: Matrix Computations in Apache Spark., , , , , , , , and . CoRR, (2015)MLlib: Machine Learning in Apache Spark., , , , , , , , , and 6 other author(s). J. Mach. Learn. Res., (2016)Exploiting Reuse in Pipeline-Aware Hyperparameter Tuning., , , and . CoRR, (2019)Automating model search for large scale machine learning., , , , , and . SoCC, page 368-380. ACM, (2015)TuPAQ: An Efficient Planner for Large-scale Predictive Analytic Queries., , , , and . CoRR, (2015)