Doris Xin

Publication Activity (10 Years)

Years Active: 2013-2022
Publications (10 Years): 25

Top Topics

Heterogeneous Information Networks

Empirical Analysis

Machine Learning

Top Venues

Proc. VLDB Endow.

SIGMOD Conference

IEEE Data Eng. Bull.

Publications

Matthias Boehm, Paroma Varma, Doris Xin
DEEM'22: Data Management for End-to-End Machine Learning. SIGMOD Conference (2022)
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)
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) (2021)
Doris Xin, Hui Miao, Aditya G. Parameswaran, Neoklis Polyzotis
Production Machine Learning Pipelines: Empirical Analysis and Optimization Opportunities. CoRR (2021)
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) (2021)
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 (2021)
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 (2021)
Doris Xin, Hui Miao, Aditya G. Parameswaran, Neoklis Polyzotis
Production Machine Learning Pipelines: Empirical Analysis and Optimization Opportunities. SIGMOD Conference (2021)
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) (2020)
Stephen Macke, Hongpu Gong, Doris Jung Lin Lee, Andrew Head, Doris Xin, Aditya G. Parameswaran
Fine-Grained Lineage for Safer Notebook Interactions. CoRR (2020)
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)
Angela Lee, Doris Xin, Doris Lee, Aditya G. Parameswaran
Demystifying a Dark Art: Understanding Real-World Machine Learning Model Development. CoRR (2020)
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 (2020)
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) (2019)
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 (2019)
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)
Doris Xin, Litian Ma, Jialin Liu, Stephen Macke, Shuchen Song, Aditya G. Parameswaran
Helix: Accelerating Human-in-the-loop Machine Learning. CoRR (2018)
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) (2018)
Doris Xin, Ahmed El-Kishky, De Liao, Brandon Norick, Jiawei Han
Active Learning on Heterogeneous Information Networks: A Multi-armed Bandit Approach. ICDM (2018)
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) (2018)
Doris Xin, Stephen Macke, Litian Ma, Jialin Liu, Shuchen Song, Aditya G. Parameswaran
Helix: Holistic Optimization for Accelerating Iterative Machine Learning. CoRR (2018)
Doris Xin, Litian Ma, Jialin Liu, Stephen Macke, Shuchen Song, Aditya G. Parameswaran
Accelerating Human-in-the-loop Machine Learning: Challenges and Opportunities. CoRR (2018)
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 (2018)
Doris Xin, Nicolas Mayoraz, Hubert Pham, Karthik Lakshmanan, John R. Anderson
Folding: Why Good Models Sometimes Make Spurious Recommendations. RecSys (2017)
Xiangrui Meng, Joseph K. Bradley, Burak Yavuz, Evan R. 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 (2016)
Xiangrui Meng, Joseph K. Bradley, Burak Yavuz, Evan R. 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 (2015)
Moya Chen, Doris Xin, Damien Woods
Parallel computation using active self-assembly. Nat. Comput. 14 (2) (2015)
Moya Chen, Doris Xin, Damien Woods
Parallel computation using active self-assembly. CoRR (2014)
Deepak Agarwal, Bo Long, Jonathan Traupman, Doris Xin, Liang Zhang
LASER: a scalable response prediction platform for online advertising. WSDM (2014)
Moya Chen, Doris Xin, Damien Woods
Parallel Computation Using Active Self-assembly. DNA (2013)