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03/30/2021
Production Machine Learning Pipelines: Empirical Analysis and Optimization Opportunities
Machine learning (ML) is now commonplace, powering data-driven applicati...
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03/03/2021
Enhancing the Interactivity of Dataframe Queries by Leveraging Think Time
We propose opportunistic evaluation, a framework for accelerating intera...
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01/13/2021
Whither AutoML? Understanding the Role of Automation in Machine Learning Workflows
Efforts to make machine learning more widely accessible have led to a ra...
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12/13/2020
Fine-Grained Lineage for Safer Notebook Interactions
Computational notebooks have emerged as the platform of choice for data ...
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05/04/2020
Demystifying a Dark Art: Understanding Real-World Machine Learning Model Development
It is well-known that the process of developing machine learning (ML) wo...
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01/03/2020
Towards Scalable Dataframe Systems
Dataframes are a popular and convenient abstraction to represent, struct...
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11/01/2019
Extending Relational Query Processing with ML Inference
The broadening adoption of machine learning in the enterprise is increas...
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12/14/2018
Helix: Holistic Optimization for Accelerating Iterative Machine Learning
Machine learning workflow development is a process of trial-and-error: d...
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08/03/2018
Helix: Accelerating Human-in-the-loop Machine Learning
Data application developers and data scientists spend an inordinate amou...
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04/16/2018
Accelerating Human-in-the-loop Machine Learning: Challenges and Opportunities
Development of machine learning (ML) workflows is a tedious process of i...
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03/27/2018
How Developers Iterate on Machine Learning Workflows -- A Survey of the Applied Machine Learning Literature
Machine learning workflow development is anecdotally regarded to be an i...
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05/26/2015