435 citations · 529 across the 13 of their papers we have counts for
3 papers · 1 filter
Justices for Information Bottleneck Theory
Faxian Cao, Yongqiang Cheng, Adil Mehmood Khan +1
This study comes as a timely response to mounting criticism of the information bottleneck (IB) theory, injecting fresh perspectives to rectify misconceptions and reaffirm its valid…
RepFair-GAN: Mitigating Representation Bias in GANs Using Gradient Clipping
Patrik Joslin Kenfack, Kamil Sabbagh, Adín Ramírez Rivera +1
Fairness has become an essential problem in many domains of Machine Learning (ML), such as classification, natural language processing, and Generative Adversarial Networks (GANs).…
On the Fairness of Generative Adversarial Networks (GANs)
Patrik Joslin Kenfack, Daniil Dmitrievich Arapov, Rasheed Hussain +2
Generative adversarial networks (GANs) are one of the greatest advances in AI in recent years. With their ability to directly learn the probability distribution of data, and then s…