Fits and Starts: Enterprise Use of AutoML and the Role of Humans in the Loop

12 January 2021

Papers citing "Fits and Starts: Enterprise Use of AutoML and the Role of Humans in the Loop"

11 / 11 papers shown

Title
Medical artificial intelligence toolbox (MAIT): an explainable machine learning framework for binary classification, survival modelling, and regression analyses Ramtin Zargari Marandi Anne Svane Frahm Jens Lundgren Daniel Dawson Murray Maja Milojevic 26 0 0 08 Jan 2025
Generative AI in the Wild: Prospects, Challenges, and Strategies Yuan Sun Eunchae Jang Fenglong Ma Ting Wang 34 21 0 03 Apr 2024
Assessing the Use of AutoML for Data-Driven Software Engineering Fabio Calefato L. Quaranta F. Lanubile Marcos Kalinowski 38 7 0 20 Jul 2023
Why is AI not a Panacea for Data Workers? An Interview Study on Human-AI Collaboration in Data Storytelling Haotian Li Yun Wang Q. V. Liao Huamin Qu 63 23 0 17 Apr 2023
Tracing and Visualizing Human-ML/AI Collaborative Processes through Artifacts of Data Work Jennifer Rogers Anamaria Crisan 32 7 0 05 Apr 2023
Addressing UX Practitioners' Challenges in Designing ML Applications: an Interactive Machine Learning Approach K. J. Kevin Feng David W. McDonald HAI 23 11 0 23 Feb 2023
AutoML in The Wild: Obstacles, Workarounds, and Expectations Yuan Sun Qiurong Song Xinning Gui Fenglong Ma Ting Wang 21 13 0 21 Feb 2023
An Empirical Study on the Usage of Automated Machine Learning Tools Forough Majidi Moses Openja Foutse Khomh Heng Li 45 14 0 28 Aug 2022
Interactive Model Cards: A Human-Centered Approach to Model Documentation Anamaria Crisan Margaret Drouhard Jesse Vig Nazneen Rajani HAI 40 87 0 05 May 2022
Naive Automated Machine Learning F. Mohr Marcel Wever 24 11 0 29 Nov 2021
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 178 308 0 05 Sep 2019