40 citations · 111 across the 17 of their papers we have counts for
12 papers · 1 filter
Preventing Discriminatory Decision-making in Evolving Data Streams
Zichong Wang, Nripsuta Saxena, Tongjia Yu +8
Bias in machine learning has rightly received significant attention over the last decade. However, most fair machine learning (fair-ML) work to address bias in decision-making syst…
Individual Fairness under Uncertainty
Wenbin Zhang, Zichong Wang, Juyong Kim +4
Algorithmic fairness, the research field of making machine learning (ML) algorithms fair, is an established area in ML. As ML technologies expand their application domains, includi…
Fair Decision-making Under Uncertainty
Wenbin Zhang, Jeremy C. Weiss
There has been concern within the artificial intelligence (AI) community and the broader society regarding the potential lack of fairness of AI-based decision-making systems. Surpr…
Longitudinal Fairness with Censorship
Wenbin Zhang, Jeremy C. Weiss
Recent works in artificial intelligence fairness attempt to mitigate discrimination by proposing constrained optimization programs that achieve parity for some fairness statistic.…
Fairness Amidst Non-IID Graph Data: A Literature Review
Wenbin Zhang, Shuigeng Zhou, Toby Walsh +1
The growing importance of understanding and addressing algorithmic bias in artificial intelligence (AI) has led to a surge in research on AI fairness, which often assumes that the…
A survey on datasets for fairness-aware machine learning
Tai Le Quy, Arjun Roy, Vasileios Iosifidis +2
As decision-making increasingly relies on Machine Learning (ML) and (big) data, the issue of fairness in data-driven Artificial Intelligence (AI) systems is receiving increasing at…
FARF: A Fair and Adaptive Random Forests Classifier
Wenbin Zhang, Albert Bifet, Xiangliang Zhang +2
As Artificial Intelligence (AI) is used in more applications, the need to consider and mitigate biases from the learned models has followed. Most works in developing fair learning…
Online Fairness-Aware Learning with Imbalanced Data Streams
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 application…
Online and Customizable Fairness-aware Learning
Wenbin Zhang
While artificial intelligence (AI)-based decision-making systems are increasingly popular, significant concerns on the potential discrimination during the AI decision-making proces…
Disentangled Dynamic Graph Deep Generation
Wenbin Zhang, Liming Zhang, Dieter Pfoser +1
Deep generative models for graphs have exhibited promising performance in ever-increasing domains such as design of molecules (i.e, graph of atoms) and structure prediction of prot…
FAHT: An Adaptive Fairness-aware Decision Tree Classifier
Wenbin Zhang, Eirini Ntoutsi
Automated data-driven decision-making systems are ubiquitous across a wide spread of online as well as offline services. These systems, depend on sophisticated learning algorithms…
A Deterministic Self-Organizing Map Approach and its Application on Satellite Data based Cloud Type Classification
Wenbin Zhang, Jianwu Wang, Daeho Jin +2
A self-organizing map (SOM) is a type of competitive artificial neural network, which projects the high-dimensional input space of the training samples into a low-dimensional space…