Doris Xin

According to our database, Doris Xin authored at least 19 papers between 2014 and 2022.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of four.

2022

DEEM'22: Data Management for End-to-End Machine Learning.

Matthias Boehm, Paroma Varma, Doris Xin

Proceedings of the SIGMOD '22: International Conference on Management of Data, Philadelphia, PA, USA, June 12, 2022

2021

Usable and Efficient Systems for Machine Learning.

Doris Xin

PhD thesis, 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

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

Production Machine Learning Pipelines: Empirical Analysis and Optimization Opportunities.

Doris Xin, Hui Miao, Aditya G. Parameswaran, Neoklis Polyzotis

Proceedings of the SIGMOD '21: International Conference on Management of Data, 2021

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

Proceedings of the CHI '21: CHI Conference on Human Factors in Computing Systems, 2021

2020

Towards Scalable Dataframe Systems.

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

Proc. VLDB Endow., 2020

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

Angela Lee, Doris Xin, Doris Lee, Aditya G. Parameswaran

CoRR, 2020

Extending Relational Query Processing with ML Inference.

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

Proceedings of the 10th Conference on Innovative Data Systems Research, 2020

2019

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

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

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

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

Accelerating Human-in-the-loop Machine Learning: Challenges and Opportunities.

Doris Xin, Litian Ma, Jialin Liu, Stephen Macke, Shuchen Song, Aditya G. Parameswaran

Proceedings of the Second Workshop on Data Management for End-To-End Machine Learning, 2018

Active Learning on Heterogeneous Information Networks: A Multi-armed Bandit Approach.

Doris Xin, Ahmed El-Kishky, De Liao, Brandon Norick, Jiawei Han

Proceedings of the IEEE International Conference on Data Mining, 2018

2017

Folding: Why Good Models Sometimes Make Spurious Recommendations.

Doris Xin, Nicolas Mayoraz, Hubert Pham, Karthik Lakshmanan, John R. Anderson

Proceedings of the Eleventh ACM Conference on Recommender Systems, 2017

2016

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, Michael J. Franklin, Reza Zadeh, Matei Zaharia, Ameet Talwalkar

J. Mach. Learn. Res., 2016

2015

Parallel computation using active self-assembly.

Moya Chen, Doris Xin, Damien Woods

Nat. Comput., 2015

2014

LASER: a scalable response prediction platform for online advertising.

Deepak Agarwal, Bo Long, Jonathan Traupman, Doris Xin, Liang Zhang

Proceedings of the Seventh ACM International Conference on Web Search and Data Mining, 2014