Production Machine Learning Pipelines: Empirical Analysis and Optimization Opportunities

30 March 2021

Papers citing "Production Machine Learning Pipelines: Empirical Analysis and Optimization Opportunities"

5 / 5 papers shown

Title
The Relational Data Borg is Learning Dan Olteanu 26 24 0 18 Aug 2020
Demystifying a Dark Art: Understanding Real-World Machine Learning Model Development Angela Lee Doris Xin D. Lee Aditya G. Parameswaran HAI 87 12 0 04 May 2020
How do Data Science Workers Collaborate? Roles, Workflows, and Tools Amy X. Zhang Michael J. Muller Dakuo Wang FedML AI4CE 64 260 0 18 Jan 2020
Extending Relational Query Processing with ML Inference Konstantinos Karanasos Matteo Interlandi Doris Xin Fotis Psallidas Rathijit Sen ... Subru Krishnan Markus Weimer Yuan Yu R. Ramakrishnan Carlo Curino 84 62 0 01 Nov 2019
Helix: Holistic Optimization for Accelerating Iterative Machine Learning Doris Xin Stephen Macke Litian Ma Jialin Liu Shuchen Song Aditya G. Parameswaran 38 60 0 14 Dec 2018