Machine Learning Evaluation: Research Area — Prolific Citations Library

Discover 2 peer-reviewed studies in Machine Learning Evaluation (2018–2022). Explore research findings powered by Prolific's diverse participant panel.

This page lists 2 peer-reviewed papers in the research area of Machine Learning Evaluation in the Prolific Citations Library, a curated collection of research powered by high-quality human data from Prolific.

Papers (2 of 2)

A framework for rigorous evaluation of human performance in human and machine learning comparison studies

Authors: HP Cowley, M Natter, K Gray-Roncal, RE Rhodes

Year: 2022

Published in: Scientific Reports, 2022 - nature.com

Institution: Johns Hopkins University Applied Physics Laboratory, University of Oxford, Johns Hopkins University, Johns Hopkins University Applied Physics Laboratory, University of Oxford, Johns Hopkins University

Research Area: Human-AI Interaction, Machine Learning Evaluation, AI Evaluation

Discipline: Human-Computer Interaction (HCI)

DOI: https://doi.org/10.1038/s41598-022-08078-3

Citations: 34
Making better use of the crowd: How crowdsourcing can advance machine learning research

Authors: JW Vaughan

Year: 2018

Published in: Journal of Machine Learning Research, 2018 - jmlr.org

Institution: Microsoft Research

Research Area: Crowdsourcing for Machine Learning Research, including data generation, model evaluation, hybrid intelligence systems, behavioral experiments.

Discipline: Machine Learning

Citations: 264