Operationalizing Machine Learning: An Interview Study

Operationalizing Machine Learning: An Interview Study

16 September 2022

J. M. Hellerstein

Aditya G. Parameswaran

Papers citing "Operationalizing Machine Learning: An Interview Study"

9 / 9 papers shown

Title
Data Makes Better Data Scientists Jinjin Zhao A. Gal Sanjay Krishnan 20 2 0 27 May 2024
Language Models Enable Simple Systems for Generating Structured Views of Heterogeneous Data Lakes Simran Arora Brandon Yang Sabri Eyuboglu A. Narayan Andrew Hojel Immanuel Trummer Christopher Ré SyDa 38 69 0 19 Apr 2023
Rethinking Streaming Machine Learning Evaluation Shreya Shankar Bernease Herman Aditya G. Parameswaran LRM 27 7 0 23 May 2022
The CLEAR Benchmark: Continual LEArning on Real-World Imagery Zhiqiu Lin Jia Shi Deepak Pathak Deva Ramanan CLL VLM 118 91 0 17 Jan 2022
A Fine-Grained Analysis on Distribution Shift Olivia Wiles Sven Gowal Florian Stimberg Sylvestre-Alvise Rebuffi Ira Ktena Krishnamurthy Dvijotham A. Cemgil OOD 215 196 0 21 Oct 2021
Whither AutoML? Understanding the Role of Automation in Machine Learning Workflows Doris Xin Eva Yiwei Wu D. Lee Niloufar Salehi Aditya G. Parameswaran 34 71 0 13 Jan 2021
Demystifying a Dark Art: Understanding Real-World Machine Learning Model Development Angela Lee Doris Xin D. Lee Aditya G. Parameswaran HAI 24 12 0 04 May 2020
Human-AI Collaboration in Data Science: Exploring Data Scientists' Perceptions of Automated AI Dakuo Wang Justin D. Weisz Michael J. Muller Parikshit Ram Werner Geyer Casey Dugan Y. Tausczik Horst Samulowitz Alexander G. Gray 153 312 0 05 Sep 2019
Improving fairness in machine learning systems: What do industry practitioners need? Kenneth Holstein Jennifer Wortman Vaughan Hal Daumé Miroslav Dudík Hanna M. Wallach FaML HAI 181 730 0 13 Dec 2018