arxiv: 1804.05892 · v1 · pith:7DHKTEADnew · submitted 2018-04-16 · 💻 cs.DB

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

Doris Xin , Litian Ma , Jialin Liu , Stephen Macke , Shuchen Song , Aditya Parameswaran This is my paper

classification 💻 cs.DB

keywords systemworkflowschangesdescribehuman-in-the-loopiterativelearningmachine

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Development of machine learning (ML) workflows is a tedious process of iterative experimentation: developers repeatedly make changes to workflows until the desired accuracy is attained. We describe our vision for a "human-in-the-loop" ML system that accelerates this process: by intelligently tracking changes and intermediate results over time, such a system can enable rapid iteration, quick responsive feedback, introspection and debugging, and background execution and automation. We finally describe Helix, our preliminary attempt at such a system that has already led to speedups of up to 10x on typical iterative workflows against competing systems.

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

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