S Agarwal - IJCAI 2021 Workshop on AI for Social Good, 2021 - projects.iq.harvard.edu
… differential privacy and fairness can be at odds with each other when we consider a learning … In particular, we consider a simple binary classification setting where the learning algorithm …
… result highlighting the incompatibility of privacy and fairness. Section 4.3 talks about some other directions we pursued along the trade-offs between privacy and fairness, and finally in …
… The focus on fairness in machinelearning and its relationship to differential privacy was explored in early work by the privacy community [7]. This work introduced the concept of treating …
Y Zhao, Y Yu, Y Li, G Han, X Du - Information Sciences, 2019 - Elsevier
… However, these mechanisms are inadequate for ensuring privacy and availability for fair … fair data trading protocol in big data market to conduct privacy-preserving, availability and fair …
… Machinelearning has changed our lives and will undoubtedly bring us more excitement. However, its success is closely tied to the availability of large-scale training data, and as …
… ML from privacy, safety, and fairness perspectives, as illustrated in Figure 1:1 Privacy: The speech-… user privacy, such as revealing sensitive information that people might want to keep …
… private deep learning. Specifically, we aim to study how different levels of imbalance in the data affect the accuracy and the fairness of … We also study the fairness metrics demographic …
D Xu, S Yuan, X Wu - Companion proceedings of The 2019 world wide …, 2019 - dl.acm.org
… requirements simultaneously in machinelearning algorithms is under exploited. In this … one classic machinelearning model, logistic regression, and develop differentially private and fair …
… Among various privacy notions, differential privacy has become … private exponential mechanism as a post-processing step to improve both fairness and privacy of supervised learning …