LASER: a scalable response prediction platform for online advertising. - Deepak Agarwal; Bo Long; Jonathan Traupman; Doris Xin; Liang Zhang 021 (WSDM, 2014)

Parallel computation using active self-assembly. - Moya Chen; Doris Xin; Damien Woods (Nat. Comput., 2015)

MLlib: Machine Learning in Apache Spark. - 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; et al. (J. Mach. Learn. Res., 2016)

Folding: Why Good Models Sometimes Make Spurious Recommendations. - Doris Xin; Nicolas Mayoraz; Hubert Pham; Karthik Lakshmanan; John R. Anderson (RecSys, 2017)

Active Learning on Heterogeneous Information Networks: A Multi-armed Bandit Approach. - Doris Xin; Ahmed El-Kishky; De Liao; Brandon Norick; Jiawei Han 001 (ICDM, 2018)

Accelerating Human-in-the-loop Machine Learning: Challenges and Opportunities. - Doris Xin; Litian Ma; Jialin Liu; Stephen Macke; Shuchen Song; Aditya G. Parameswaran (DEEM@SIGMOD, 2018)

How Developers Iterate on Machine Learning Workflows - A Survey of the Applied Machine Learning Literature. - Doris Xin; Litian Ma; Shuchen Song; Aditya G. Parameswaran (CoRR, 2018)

Helix: Accelerating Human-in-the-loop Machine Learning. - Doris Xin; Litian Ma; Jialin Liu; Stephen Macke; Shuchen Song; Aditya G. Parameswaran (Proc. VLDB Endow., 2018)

Helix: Holistic Optimization for Accelerating Iterative Machine Learning. - Doris Xin; Stephen Macke; Litian Ma; Jialin Liu; Shuchen Song; Aditya G. Parameswaran (Proc. VLDB Endow., 2018)

A Human-in-the-loop Perspective on AutoML: Milestones and the Road Ahead. - Doris Jung Lin Lee; Stephen Macke; Doris Xin; Angela Lee; Silu Huang; Aditya G. Parameswaran (IEEE Data Eng. Bull., 2019)

Extending Relational Query Processing with ML Inference. - Konstantinos Karanasos; Matteo Interlandi; Fotis Psallidas; Rathijit Sen; Kwanghyun Park 001; Ivan Popivanov; Doris Xin; Supun Nakandala; Subru Krishnan; Markus Weimer; Yuan Yu; Raghu Ramakrishnan 001; et al. (CIDR, 2020)

Demystifying a Dark Art: Understanding Real-World Machine Learning Model Development. - Angela Lee; Doris Xin; Doris Lee; Aditya G. Parameswaran (CoRR, 2020)

Towards Scalable Dataframe Systems. - Devin Petersohn; William W. Ma; Doris Jung Lin Lee; Stephen Macke; Doris Xin; Xiangxi Mo; Joseph Gonzalez 001; Joseph M. Hellerstein; Anthony D. Joseph; Aditya G. Parameswaran (Proc. VLDB Endow., 2020)

Whither AutoML? Understanding the Role of Automation in Machine Learning Workflows. - Doris Xin; Eva Yiwei Wu; Doris Jung Lin Lee; Niloufar Salehi; Aditya G. Parameswaran (CHI, 2021)

Production Machine Learning Pipelines: Empirical Analysis and Optimization Opportunities. - Doris Xin; Hui Miao; Aditya G. Parameswaran; Neoklis Polyzotis (SIGMOD Conference, 2021)

Enhancing the Interactivity of Dataframe Queries by Leveraging Think Time. - Doris Xin; Devin Petersohn; Dixin Tang; Yifan Wu; Joseph E. Gonzalez; Joseph M. Hellerstein; Anthony D. Joseph; Aditya G. Parameswaran (IEEE Data Eng. Bull., 2021)

Fine-Grained Lineage for Safer Notebook Interactions. - Stephen Macke; Aditya G. Parameswaran; Hongpu Gong; Doris Jung Lin Lee; Doris Xin; Andrew Head (Proc. VLDB Endow., 2021)

Usable and Efficient Systems for Machine Learning. - Doris Xin (2021)

DEEM'22: Data Management for End-to-End Machine Learning. - Matthias Boehm 001; Paroma Varma; Doris Xin (SIGMOD Conference, 2022)