The Grind for Good Data: Understanding ML Practitioners' Struggles and Aspirations in Making Good Data

28 November 2022

Papers citing "The Grind for Good Data: Understanding ML Practitioners' Struggles and Aspirations in Making Good Data"

5 / 5 papers shown

Title
Towards Scenario- and Capability-Driven Dataset Development and Evaluation: An Approach in the Context of Mapless Automated Driving Felix Grün Marcus Nolte Markus Maurer 27 1 0 30 Apr 2024
Whose AI Dream? In search of the aspiration in data annotation Ding-wen Wang Shantanu Prabhat Nithya Sambasivan 166 57 0 21 Mar 2022
Whither AutoML? Understanding the Role of Automation in Machine Learning Workflows Doris Xin Eva Yiwei Wu D. Lee Niloufar Salehi Aditya G. Parameswaran 48 91 0 13 Jan 2021
AutoML to Date and Beyond: Challenges and Opportunities Shubhra (Santu) Karmaker Md. Mahadi Hassan Micah J. Smith Lei Xu Chengxiang Zhai K. Veeramachaneni 66 222 0 21 Oct 2020
A Survey on Bias and Fairness in Machine Learning Ninareh Mehrabi Fred Morstatter N. Saxena Kristina Lerman Aram Galstyan SyDa FaML 294 4,187 0 23 Aug 2019