2 code implementations • 10 Nov 2022 • Suvodeep Majumder, Joymallya Chakraborty, Tim Menzies
Hence, there are often limits on how much-labeled data is available for training.
1 code implementation • 3 Nov 2021 • Joymallya Chakraborty, Suvodeep Majumder, Huy Tu
Semi-supervised learning is a machine learning technique where, incrementally, labeled data is used to generate pseudo-labels for the rest of the data (and then all that data is used for model training).
1 code implementation • 25 Oct 2021 • Suvodeep Majumder, Joymallya Chakraborty, Gina R. Bai, Kathryn T. Stolee, Tim Menzies
In summary, to simplify the fairness testing problem, we recommend the following steps: (1)~determine what type of fairness is desirable (and we offer a handful of such types); then (2) lookup those types in our clusters; then (3) just test for one item per cluster.
no code implementations • 3 Oct 2021 • Kewen Peng, Joymallya Chakraborty, Tim Menzies
Our approach aims to offset the biased predictions of the classification model via rebalancing the distribution of protected attributes.
1 code implementation • 17 Jul 2021 • Zhe Yu, Joymallya Chakraborty, Tim Menzies
We found that equalizing the class distribution in each demographic group with sample weights is a necessary condition for achieving equalized odds without modifying the normal training process.
2 code implementations • 25 May 2021 • Joymallya Chakraborty, Suvodeep Majumder, Tim Menzies
This paper postulates that the root causes of bias are the prior decisions that affect- (a) what data was selected and (b) the labels assigned to those examples.
no code implementations • 14 May 2019 • Joymallya Chakraborty, Tianpei Xia, Fahmid M. Fahid, Tim Menzies
To the best of our knowledge, this is the first application of hyperparameter optimization as a tool for software engineers to generate fairer software.