Doris Xin

According to our database1, Doris Xin authored at least 19 papers between 2014 and 2022.

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Bibliography

2022
DEEM'22: Data Management for End-to-End Machine Learning.
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.
PhD thesis, 2021

Fine-Grained Lineage for Safer Notebook Interactions.
Proc. VLDB Endow., 2021

Enhancing the Interactivity of Dataframe Queries by Leveraging Think Time.
IEEE Data Eng. Bull., 2021

Production Machine Learning Pipelines: Empirical Analysis and Optimization Opportunities.
Proceedings of the SIGMOD '21: International Conference on Management of Data, 2021

Whither AutoML? Understanding the Role of Automation in Machine Learning Workflows.
Proceedings of the CHI '21: CHI Conference on Human Factors in Computing Systems, 2021

2020
Towards Scalable Dataframe Systems.
Proc. VLDB Endow., 2020

Demystifying a Dark Art: Understanding Real-World Machine Learning Model Development.
CoRR, 2020

Extending Relational Query Processing with ML Inference.
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.
IEEE Data Eng. Bull., 2019

2018
Helix: Holistic Optimization for Accelerating Iterative Machine Learning.
Proc. VLDB Endow., 2018

Helix: Accelerating Human-in-the-loop Machine Learning.
Proc. VLDB Endow., 2018

How Developers Iterate on Machine Learning Workflows - A Survey of the Applied Machine Learning Literature.
CoRR, 2018

Accelerating Human-in-the-loop Machine Learning: Challenges and Opportunities.
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.
Proceedings of the IEEE International Conference on Data Mining, 2018

2017
Folding: Why Good Models Sometimes Make Spurious Recommendations.
Proceedings of the Eleventh ACM Conference on Recommender Systems, 2017

2016
MLlib: Machine Learning in Apache Spark.
J. Mach. Learn. Res., 2016

2015
Parallel computation using active self-assembly.
Nat. Comput., 2015

2014
LASER: a scalable response prediction platform for online advertising.
Proceedings of the Seventh ACM International Conference on Web Search and Data Mining, 2014


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