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Learning to Grade Student Programs in a Massive Open Online Course.

, , , , , and . ICDM, page 785-790. IEEE Computer Society, (2014)

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History-aware query optimization with materialized intermediate views., and . ICDE, page 520-531. IEEE Computer Society, (2014)A comparison of platforms for implementing and running very large scale machine learning algorithms., , , , , and . SIGMOD Conference, page 1371-1382. ACM, (2014)Online Random Shuffling of Large Database Tables.. IEEE Trans. Knowl. Data Eng., 19 (1): 73-84 (2007)Mixture models for learning low-dimensional roles in high-dimensional data., , and . KDD, page 909-918. ACM, (2010)Scalable Linear Algebra on a Relational Database System., , , , and . ICDE, page 523-534. IEEE Computer Society, (2017)Declarative Parameterizations of User-Defined Functions for Large-Scale Machine Learning and Optimization., , and . IEEE Trans. Knowl. Data Eng., 31 (11): 2079-2092 (2019)Parallel and Distributed MCMC via Shepherding Distributions., and . AISTATS, volume 84 of Proceedings of Machine Learning Research, page 1819-1827. PMLR, (2018)Learning correlations using the mixture-of-subsets model., , and . ACM Trans. Knowl. Discov. Data, 1 (4): 3:1-3:42 (2008)Do Anesthesiologists Know What They Are Doing? Mining a Surgical Time-Series Database to Correlate Expert Assessment with Outcomes., , , and . ACM Trans. Knowl. Discov. Data, 10 (3): 24:1-24:27 (2016)Materialized Sample Views for Database Approximation., and . IEEE Trans. Knowl. Data Eng., 20 (3): 337-351 (2008)