69 citations · 136 across the 49 of their papers we have counts for
5 papers · 1 filter
A Unifying Generator Loss Function for Generative Adversarial Networks
Justin Veiner, Fady Alajaji, Bahman Gharesifard
A unifying -parametrized generator loss function is introduced for a dual-objective generative adversarial network (GAN), which uses a canonical (or classical) discriminator los…
Classification Utility, Fairness, and Compactness via Tunable Information Bottleneck and Rényi Measures
Adam Gronowski, William Paul, Fady Alajaji +2
Designing machine learning algorithms that are accurate yet fair, not discriminating based on any sensitive attribute, is of paramount importance for society to accept AI for criti…
Renyi Fair Information Bottleneck for Image Classification
Adam Gronowski, William Paul, Fady Alajaji +2
We develop a novel method for ensuring fairness in machine learning which we term as the Renyi Fair Information Bottleneck (RFIB). We consider two different fairness constraints -…
TARA: Training and Representation Alteration for AI Fairness and Domain Generalization
William Paul, Armin Hadzic, Neil Joshi +2
We propose a novel method for enforcing AI fairness with respect to protected or sensitive factors. This method uses a dual strategy performing training and representation alterati…
Least th-Order and Rényi Generative Adversarial Networks
Himesh Bhatia, William Paul, Fady Alajaji +2
We investigate the use of parametrized families of information-theoretic measures to generalize the loss functions of generative adversarial networks (GANs) with the objective of i…