2 citations · 3 across the 5 of their papers we have counts for
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cs.LG2023
Using linear initialisation to improve speed of convergence and fully-trained error in Autoencoders
Marcel Marais, Mate Hartstein, George Cevora
Good weight initialisation is an important step in successful training of Artificial Neural Networks. Over time a number of improvements have been proposed to this process. In this…
cs.LG2020
Demonstrating Rosa: the fairness solution for any Data Analytic pipeline
Kate Wilkinson, George Cevora
Most datasets of interest to the analytics industry are impacted by various forms of human bias. The outcomes of Data Analytics [DA] or Machine Learning [ML] on such data are there…
cs.LG2020★ 1 cited
Fair Adversarial Networks
George Cevora
The influence of human judgement is ubiquitous in datasets used across the analytics industry, yet humans are known to be sub-optimal decision makers prone to various biases. Analy…