Designing Evaluations of Machine Learning Models for Subjective Inference: The Case of Sentence Toxicity

6 November 2019

Papers citing "Designing Evaluations of Machine Learning Models for Subjective Inference: The Case of Sentence Toxicity"

6 / 6 papers shown

Title
AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias Rachel K. E. Bellamy Kuntal Dey Michael Hind Samuel C. Hoffman Stephanie Houde ... Diptikalyan Saha P. Sattigeri Moninder Singh Kush R. Varshney Yunfeng Zhang FaML SyDa 96 806 0 03 Oct 2018
Datasheets for Datasets Timnit Gebru Jamie Morgenstern Briana Vecchione Jennifer Wortman Vaughan Hanna M. Wallach Hal Daumé Kate Crawford 258 2,178 0 23 Mar 2018
On Formalizing Fairness in Prediction with Machine Learning Pratik Gajane Mykola Pechenizkiy FaML 157 211 0 09 Oct 2017
Like trainer, like bot? Inheritance of bias in algorithmic content moderation Reuben Binns Michael Veale Max Van Kleek N. Shadbolt 35 147 0 05 Jul 2017
Ex Machina: Personal Attacks Seen at Scale Ellery Wulczyn Nithum Thain Lucas Dixon 86 757 0 27 Oct 2016
Massive Online Crowdsourced Study of Subjective and Objective Picture Quality Deepti Ghadiyaram A. Bovik 55 660 0 09 Nov 2015