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On Automatic Feasibility Study for Machine Learning Application Development with ease.ml/snoopy

Oct 16, 2020
Cedric Renggli, Luka Rimanic, Luka Kolar, Nora Hollenstein, Wentao Wu, Ce Zhang


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Nearest Neighbor Classifiers over Incomplete Information: From Certain Answers to Certain Predictions

May 12, 2020
Bojan Karlaš, Peng Li, Renzhi Wu, Nezihe Merve Gürel, Xu Chu, Wentao Wu, Ce Zhang


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Data Science through the looking glass and what we found there

Dec 19, 2019
Fotis Psallidas, Yiwen Zhu, Bojan Karlas, Matteo Interlandi, Avrilia Floratou, Konstantinos Karanasos, Wentao Wu, Ce Zhang, Subru Krishnan, Carlo Curino, Markus Weimer


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Quantitative Overfitting Management for Human-in-the-loop ML Application Development with ease.ml/meter

Jun 06, 2019
Frances Ann Hubis, Wentao Wu, Ce Zhang


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Continuous Integration of Machine Learning Models with ease.ml/ci: Towards a Rigorous Yet Practical Treatment

Mar 01, 2019
Cedric Renggli, Bojan Karlaš, Bolin Ding, Feng Liu, Kevin Schawinski, Wentao Wu, Ce Zhang


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MLBench: How Good Are Machine Learning Clouds for Binary Classification Tasks on Structured Data?

Oct 16, 2017
Yu Liu, Hantian Zhang, Luyuan Zeng, Wentao Wu, Ce Zhang


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Ease.ml: Towards Multi-tenant Resource Sharing for Machine Learning Workloads

Aug 24, 2017
Tian Li, Jie Zhong, Ji Liu, Wentao Wu, Ce Zhang


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Revisiting Differentially Private Regression: Lessons From Learning Theory and their Consequences

Dec 20, 2015
Xi Wu, Matthew Fredrikson, Wentao Wu, Somesh Jha, Jeffrey F. Naughton


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