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Production Machine Learning Pipelines: Empirical Analysis and Optimization Opportunities


Mar 30, 2021
Doris Xin, Hui Miao, Aditya Parameswaran, Neoklis Polyzotis

* Proceedings of the 2021 International Conference on Management of Data 

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Whither AutoML? Understanding the Role of Automation in Machine Learning Workflows


Jan 13, 2021
Doris Xin, Eva Yiwei Wu, Doris Jung-Lin Lee, Niloufar Salehi, Aditya Parameswaran


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Demystifying a Dark Art: Understanding Real-World Machine Learning Model Development


May 04, 2020
Angela Lee, Doris Xin, Doris Lee, Aditya Parameswaran


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Extending Relational Query Processing with ML Inference


Nov 01, 2019
Konstantinos Karanasos, Matteo Interlandi, Doris Xin, Fotis Psallidas, Rathijit Sen, Kwanghyun Park, Ivan Popivanov, Supun Nakandal, Subru Krishnan, Markus Weimer, Yuan Yu, Raghu Ramakrishnan, Carlo Curino


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Helix: Holistic Optimization for Accelerating Iterative Machine Learning


Dec 14, 2018
Doris Xin, Stephen Macke, Litian Ma, Jialin Liu, Shuchen Song, Aditya Parameswaran


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Helix: Accelerating Human-in-the-loop Machine Learning


Aug 03, 2018
Doris Xin, Litian Ma, Jialin Liu, Stephen Macke, Shuchen Song, Aditya Parameswaran


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How Developers Iterate on Machine Learning Workflows -- A Survey of the Applied Machine Learning Literature


May 17, 2018
Doris Xin, Litian Ma, Shuchen Song, Aditya Parameswaran


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MLlib: Machine Learning in Apache Spark


May 26, 2015
Xiangrui Meng, Joseph Bradley, Burak Yavuz, Evan Sparks, Shivaram Venkataraman, Davies Liu, Jeremy Freeman, DB Tsai, Manish Amde, Sean Owen, Doris Xin, Reynold Xin, Michael J. Franklin, Reza Zadeh, Matei Zaharia, Ameet Talwalkar


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Parallel computation using active self-assembly


Sep 05, 2014
Moya Chen, Doris Xin, Damien Woods

* Journal version to appear in Natural Computing. Earlier conference version appeared at DNA19 

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