no code implementations • 9 Nov 2022 • Maryam Badar, Marco Fisichella, Vasileios Iosifidis, Wolfgang Nejdl
In this context, we propose a novel adaptation of Na\"ive Bayes to mitigate discrimination embedded in the streams while maintaining high predictive performance for both the majority and minority classes.
1 code implementation • 17 Sep 2022 • Vasileios Iosifidis, Symeon Papadopoulos, Bodo Rosenhahn, Eirini Ntoutsi
Class imbalance poses a major challenge for machine learning as most supervised learning models might exhibit bias towards the majority class and under-perform in the minority class.
no code implementations • 4 Jan 2022 • Vasileios Iosifidis, Arjun Roy, Eirini Ntoutsi
Data-driven AI systems can lead to discrimination on the basis of protected attributes like gender or race.
1 code implementation • 1 Oct 2021 • Tai Le Quy, Arjun Roy, Vasileios Iosifidis, Wenbin Zhang, Eirini Ntoutsi
For a deeper understanding of bias in the datasets, we investigate the interesting relationships using exploratory analysis.
no code implementations • 13 Aug 2021 • Vasileios Iosifidis, Wenbin Zhang, Eirini Ntoutsi
Data-driven learning algorithms are employed in many online applications, in which data become available over time, like network monitoring, stock price prediction, job applications, etc.
no code implementations • 27 Apr 2021 • Arjun Roy, Vasileios Iosifidis, Eirini Ntoutsi
Recent studies showed that datasets used in fairness-aware machine learning for multiple protected attributes (referred to as multi-discrimination hereafter) are often imbalanced.
no code implementations • 27 Mar 2021 • Xin Huang, Wenbin Zhang, Xuejiao Tang, Mingli Zhang, Jayachander Surbiryala, Vasileios Iosifidis, Zhen Liu, Ji Zhang
Recent studies in big data analytics and natural language processing develop automatic techniques in analyzing sentiment in the social media information.
no code implementations • 6 Dec 2020 • Xuejiao Tang, Jiong Qiu, Ruijun Chen, Wenbin Zhang, Vasileios Iosifidis, Zhen Liu, Wei Meng, Mingli Zhang, Ji Zhang
An ideal safe workplace is described as a place where staffs fulfill responsibilities in a well-organized order, potential hazardous events are being monitored in real-time, as well as the number of accidents and relevant damages are minimized.
no code implementations • 6 Dec 2020 • Xuejiao Tang, Liuhua Zhang, Wenbin Zhang, Xin Huang, Vasileios Iosifidis, Zhen Liu, Mingli Zhang, Enza Messina, Ji Zhang
Early detection of breast cancer in X-ray mammography is believed to have effectively reduced the mortality rate.
1 code implementation • 5 Apr 2020 • Tongxin Hu, Vasileios Iosifidis, Wentong Liao, Hang Zhang, Michael YingYang, Eirini Ntoutsi, Bodo Rosenhahn
In this paper, we propose FairNN a neural network that performs joint feature representation and classification for fairness-aware learning.
no code implementations • 3 Feb 2020 • Vasileios Iosifidis, Besnik Fetahu, Eirini Ntoutsi
In the post-processing step, we tackle the problem of class overlapping by shifting the decision boundary in the direction of fairness.
1 code implementation • 17 Sep 2019 • Vasileios Iosifidis, Eirini Ntoutsi
The widespread use of ML-based decision making in domains with high societal impact such as recidivism, job hiring and loan credit has raised a lot of concerns regarding potential discrimination.
no code implementations • 16 Jul 2019 • Vasileios Iosifidis, Thi Ngoc Han Tran, Eirini Ntoutsi
The wide spread usage of automated data-driven decision support systems has raised a lot of concerns regarding accountability and fairness of the employed models in the absence of human supervision.
no code implementations • 23 Oct 2018 • Nilamadhaba Mohapatra, Vasileios Iosifidis, Asif Ekbal, Stefan Dietze, Pavlos Fafalios
Entity relatedness has emerged as an important feature in a plethora of applications such as information retrieval, entity recommendation and entity linking.