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Stochastic Gradient Descent without Full Data Shuffle


Jun 12, 2022
Lijie Xu, Shuang Qiu, Binhang Yuan, Jiawei Jiang, Cedric Renggli, Shaoduo Gan, Kaan Kara, Guoliang Li, Ji Liu, Wentao Wu, Jieping Ye, Ce Zhang

* This technical report is an extension of our SIGMOD 2022 paper titled "In-Database Machine Learning with CorgiPile: Stochastic Gradient Descent without Full Data Shuffle". https://doi.org/10.1145/3514221.3526150 

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Data Debugging with Shapley Importance over End-to-End Machine Learning Pipelines


Apr 26, 2022
Bojan Karlaš, David Dao, Matteo Interlandi, Bo Li, Sebastian Schelter, Wentao Wu, Ce Zhang


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VolcanoML: Speeding up End-to-End AutoML via Scalable Search Space Decomposition


Jul 20, 2021
Yang Li, Yu Shen, Wentao Zhang, Jiawei Jiang, Bolin Ding, Yaliang Li, Jingren Zhou, Zhi Yang, Wentao Wu, Ce Zhang, Bin Cui

* 47th International Conference on Very Large Data Bases, VLDB 2021, PVLDB Volume 14, Issue 11 

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OpenBox: A Generalized Black-box Optimization Service


Jun 06, 2021
Yang Li, Yu Shen, Wentao Zhang, Yuanwei Chen, Huaijun Jiang, Mingchao Liu, Jiawei Jiang, Jinyang Gao, Wentao Wu, Zhi Yang, Ce Zhang, Bin Cui

* Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD-2021) 

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Towards Demystifying Serverless Machine Learning Training


May 17, 2021
Jiawei Jiang, Shaoduo Gan, Yue Liu, Fanlin Wang, Gustavo Alonso, Ana Klimovic, Ankit Singla, Wentao Wu, Ce Zhang


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A Data Quality-Driven View of MLOps


Feb 15, 2021
Cedric Renggli, Luka Rimanic, Nezihe Merve Gürel, Bojan Karlaš, Wentao Wu, Ce Zhang


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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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