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Books and Theses
- 2021
[b1]Doris Xin:
Usable and Efficient Systems for Machine Learning. University of California, Berkeley, USA, 2021
Journal Articles
- 2021
- [j8]Doris Xin, Devin Petersohn, Dixin Tang, Yifan Wu, Joseph E. Gonzalez, Joseph M. Hellerstein, Anthony D. Joseph, Aditya G. Parameswaran
:
Enhancing the Interactivity of Dataframe Queries by Leveraging Think Time. IEEE Data Eng. Bull. 44(1): 66-78 (2021) - [j7]Stephen Macke, Aditya G. Parameswaran, Hongpu Gong, Doris Jung Lin Lee, Doris Xin, Andrew Head:
Fine-Grained Lineage for Safer Notebook Interactions. Proc. VLDB Endow. 14(6): 1093-1101 (2021) - 2020
- [j6]Devin Petersohn, William W. Ma, Doris Jung Lin Lee, Stephen Macke, Doris Xin, Xiangxi Mo, Joseph Gonzalez, Joseph M. Hellerstein, Anthony D. Joseph, Aditya G. Parameswaran:
Towards Scalable Dataframe Systems. Proc. VLDB Endow. 13(11): 2033-2046 (2020) - 2019
- [j5]Doris Jung Lin Lee, Stephen Macke, Doris Xin, Angela Lee, Silu Huang, Aditya G. Parameswaran:
A Human-in-the-loop Perspective on AutoML: Milestones and the Road Ahead. IEEE Data Eng. Bull. 42(2): 59-70 (2019) - 2018
- [j4]Doris Xin, Litian Ma, Jialin Liu, Stephen Macke, Shuchen Song, Aditya G. Parameswaran:
Helix: Accelerating Human-in-the-loop Machine Learning. Proc. VLDB Endow. 11(12): 1958-1961 (2018) - [j3]Doris Xin, Stephen Macke, Litian Ma, Jialin Liu, Shuchen Song, Aditya G. Parameswaran:
Helix: Holistic Optimization for Accelerating Iterative Machine Learning. Proc. VLDB Endow. 12(4): 446-460 (2018) - 2016
- [j2]Xiangrui Meng, Joseph K. Bradley, Burak Yavuz, Evan Randall Sparks, Shivaram Venkataraman, Davies Liu, Jeremy Freeman, D. B. Tsai, Manish Amde, Sean Owen, Doris Xin, Reynold Xin, Michael J. Franklin, Reza Zadeh, Matei Zaharia, Ameet Talwalkar:
MLlib: Machine Learning in Apache Spark. J. Mach. Learn. Res. 17: 34:1-34:7 (2016) - 2015
- [j1]Moya Chen, Doris Xin, Damien Woods:
Parallel computation using active self-assembly. Nat. Comput. 14(2): 225-250 (2015)
Conference and Workshop Papers
- 2022
- [c9]Matthias Boehm, Paroma Varma, Doris Xin:
DEEM'22: Data Management for End-to-End Machine Learning. SIGMOD Conference 2022: 2548-2549 - 2021
- [c8]Doris Xin, Eva Yiwei Wu, Doris Jung Lin Lee, Niloufar Salehi, Aditya G. Parameswaran:
Whither AutoML? Understanding the Role of Automation in Machine Learning Workflows. CHI 2021: 83:1-83:16 - [c7]Doris Xin, Hui Miao, Aditya G. Parameswaran, Neoklis Polyzotis:
Production Machine Learning Pipelines: Empirical Analysis and Optimization Opportunities. SIGMOD Conference 2021: 2639-2652 - 2020
- [c6]Konstantinos Karanasos, Matteo Interlandi, Fotis Psallidas, Rathijit Sen, Kwanghyun Park, Ivan Popivanov, Doris Xin, Supun Nakandala, Subru Krishnan, Markus Weimer, Yuan Yu, Raghu Ramakrishnan, Carlo Curino:
Extending Relational Query Processing with ML Inference. CIDR 2020 - 2018
- [c5]Doris Xin, Ahmed El-Kishky, De Liao, Brandon Norick, Jiawei Han:
Active Learning on Heterogeneous Information Networks: A Multi-armed Bandit Approach. ICDM 2018: 1350-1355 - [c4]Doris Xin, Litian Ma, Jialin Liu, Stephen Macke, Shuchen Song, Aditya G. Parameswaran:
Accelerating Human-in-the-loop Machine Learning: Challenges and Opportunities. DEEM@SIGMOD 2018: 9:1-9:4 - 2017
- [c3]Doris Xin, Nicolas Mayoraz, Hubert Pham, Karthik Lakshmanan, John R. Anderson:
Folding: Why Good Models Sometimes Make Spurious Recommendations. RecSys 2017: 201-209 - 2014
- [c2]Deepak Agarwal, Bo Long, Jonathan Traupman, Doris Xin, Liang Zhang:
LASER: a scalable response prediction platform for online advertising. WSDM 2014: 173-182 - 2013
- [c1]Moya Chen, Doris Xin, Damien Woods:
Parallel Computation Using Active Self-assembly. DNA 2013: 16-30
Editorship
- 2022
- [e1]Matthias Boehm, Paroma Varma, Doris Xin:
DEEM '22: Proceedings of the Sixth Workshop on Data Management for End-To-End Machine Learning Philadelphia, PA, USA, 12 June 2022. ACM 2022, ISBN 978-1-4503-9375-1 [contents]
Informal and Other Publications
- 2021
- [i13]Doris Xin, Eva Yiwei Wu, Doris Jung Lin Lee, Niloufar Salehi, Aditya G. Parameswaran:
Whither AutoML? Understanding the Role of Automation in Machine Learning Workflows. CoRR abs/2101.04834 (2021) - [i12]Doris Xin, Devin Petersohn, Dixin Tang, Yifan Wu, Joseph E. Gonzalez, Joseph M. Hellerstein, Anthony D. Joseph, Aditya G. Parameswaran:
Enhancing the Interactivity of Dataframe Queries by Leveraging Think Time. CoRR abs/2103.02145 (2021) - [i11]Doris Xin, Hui Miao, Aditya G. Parameswaran, Neoklis Polyzotis:
Production Machine Learning Pipelines: Empirical Analysis and Optimization Opportunities. CoRR abs/2103.16007 (2021) - 2020
- [i10]Devin Petersohn, William W. Ma, Doris Jung Lin Lee, Stephen Macke, Doris Xin, Xiangxi Mo, Joseph E. Gonzalez, Joseph M. Hellerstein, Anthony D. Joseph, Aditya G. Parameswaran:
Towards Scalable Dataframe Systems. CoRR abs/2001.00888 (2020) - [i9]Angela Lee, Doris Xin, Doris Lee, Aditya G. Parameswaran:
Demystifying a Dark Art: Understanding Real-World Machine Learning Model Development. CoRR abs/2005.01520 (2020) - [i8]Stephen Macke, Hongpu Gong, Doris Jung Lin Lee, Andrew Head, Doris Xin, Aditya G. Parameswaran:
Fine-Grained Lineage for Safer Notebook Interactions. CoRR abs/2012.06981 (2020) - 2019
- [i7]Konstantinos Karanasos, Matteo Interlandi, Doris Xin, Fotis Psallidas, Rathijit Sen, Kwanghyun Park, Ivan Popivanov, Supun Nakandala, Subru Krishnan, Markus Weimer, Yuan Yu, Raghu Ramakrishnan, Carlo Curino:
Extending Relational Query Processing with ML Inference. CoRR abs/1911.00231 (2019) - 2018
- [i6]Doris Xin, Litian Ma, Shuchen Song, Aditya G. Parameswaran:
How Developers Iterate on Machine Learning Workflows - A Survey of the Applied Machine Learning Literature. CoRR abs/1803.10311 (2018) - [i5]Doris Xin, Litian Ma, Jialin Liu, Stephen Macke, Shuchen Song, Aditya G. Parameswaran:
Accelerating Human-in-the-loop Machine Learning: Challenges and Opportunities. CoRR abs/1804.05892 (2018) - [i4]Doris Xin, Litian Ma, Jialin Liu, Stephen Macke, Shuchen Song, Aditya G. Parameswaran:
Helix: Accelerating Human-in-the-loop Machine Learning. CoRR abs/1808.01095 (2018) - [i3]Doris Xin, Stephen Macke, Litian Ma, Jialin Liu, Shuchen Song, Aditya G. Parameswaran:
Helix: Holistic Optimization for Accelerating Iterative Machine Learning. CoRR abs/1812.05762 (2018) - 2015
- [i2]Xiangrui Meng, Joseph K. Bradley, Burak Yavuz, Evan Randall Sparks, Shivaram Venkataraman, Davies Liu, Jeremy Freeman, D. B. Tsai, Manish Amde, Sean Owen, Doris Xin, Reynold Xin, Michael J. Franklin, Reza Zadeh, Matei Zaharia, Ameet Talwalkar:
MLlib: Machine Learning in Apache Spark. CoRR abs/1505.06807 (2015) - 2014
- [i1]Moya Chen, Doris Xin, Damien Woods:
Parallel computation using active self-assembly. CoRR abs/1405.0527 (2014)
Coauthor Index
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