A Review on Fairness in Machine Learning An increasing number of decisions regarding the daily lives of human beings are being controlled by artificial intelligence and machine learning (ML) algor... PessachDana,ShmueliErez - 《Acm Computing Surveys》 被引量: 0发表: 2022年 加载更多0关于...
There is significant literature on approaches to mitigate bias and promote fairness, yet the area is complex and hard to penetrate for newcomers to the domain. This article seeks to provide an overview of the different schools of thought and approaches to mitigating (social) biases and increase ...
基本信息论文名:Fairness in Machine Learning: A Survey 作者:Simon Caton, Christian Haas 发布时间:2024-04-09 引用次数: 670 (截止到2024年10月29)刊物: ACM Computing Surveys, Volume 56, Issue 7 Art…
Research on fairness in machine learning (ML) has been largely focusing on individual and group fairness. With the adoption of ML-based technologies as ass
Maximal Correlation for Fairness 3.1 For Discrete Learning 首先看离散变量的情况。使用Divergence Tranfer matrix(DTM)-based方法来解决离散情形下的最大相关性问题。 Def 3.1 第(y, x)个DTM \mathbf{B}_{Y,X}\in\mathbb{R}^{|\cal{Y}|,|\cal{X}|} 在联合分布 P_{X,Y} 给定时如下: \mathbf{B...
bias; algorithms; machine learning; artificial intelligence; literature review 1. Introduction Bias is the tendency to promote prejudiced results due to erroneous assumptions. In the context of ML and AI in general, this could be caused due to erroneous data on which an ML model has been ...
Please review our CONTRIBUTING.md requirements when submitting a PR to help us keep the list clean and up-to-date - thank you to the community for supporting its steady growth 🚀10 Min Video OverviewThis 10 minute video provides an overview of the motivations for machine learning operations ...
We review the emerging literature on fairness-aware machine learning and then discuss various strategic decisions that humans need to make, such as ... G Adomavicius,M Yang - 《Acm Transactions on Management Information Systems》 被引量: 0发表: 2022年 FAE: A Fairness-Aware Ensemble Framework ...
Trust in Machine Learning (Varshney, K., 2022) Safety Privacy Drift Fairness Interpretability Explainability Interpretable AI (Thampi, A., 2022) Explainability Fairness Interpretability AI Fairness (Mahoney, T., Varshney, K.R., Hind, M., 2020 Report Fairness Practical Fairness (Nielsen, A., 2021...
【论文阅读笔记】A Review on Explainability in Multimodal Deep Neural Nets, 2021 摘要 由深度神经网络驱动的人工智能技术已经在几个应用领域取得了巨大的成功,其中最重要的是在计算机视觉应用程序和自然语言处理任务中。超越人类层面的表现推动了应用领域的研究,其中语言、视觉、感官、文本之间的不同模式在准确预测和...