Quantifying fairness of federated learning LPPM models

Author:

Salem Amina Ben1,Khalfoun Besma1,Mokhtar Sonia Ben1,Mashhadi Afra2

Affiliation:

1. INSA Lyon, Lyon, France

2. University of Washington

Publisher

ACM

Reference15 articles.

1. Sarah Bird , Miro Dudík , Richard Edgar , Brandon Horn , Roman Lutz , Vanessa Milan , Mehrnoosh Sameki , Hanna Wallach , and Kathleen Walker . 2020 . Fairlearn: A toolkit for assessing and improving fairness in AI. Microsoft, Tech. Rep. MSR-TR-2020-32 (2020). Sarah Bird, Miro Dudík, Richard Edgar, Brandon Horn, Roman Lutz, Vanessa Milan, Mehrnoosh Sameki, Hanna Wallach, and Kathleen Walker. 2020. Fairlearn: A toolkit for assessing and improving fairness in AI. Microsoft, Tech. Rep. MSR-TR-2020-32 (2020).

2. Danielle L Ferreira , Bruno AA Nunes , Carlos Alberto V Campos, and Katia Obraczka. 2020 . A Deep Learning Approach for Identifying User Communities Based on Geographical Preferences and Its Applications to Urban and Environmental Planning . 6, 3 (2020), 1--24. Danielle L Ferreira, Bruno AA Nunes, Carlos Alberto V Campos, and Katia Obraczka. 2020. A Deep Learning Approach for Identifying User Communities Based on Geographical Preferences and Its Applications to Urban and Environmental Planning. 6, 3 (2020), 1--24.

3. Federated Learning in Smart City Sensing;Jiang Ji Chu;Challenges and Opportunities. Sensors,2020

4. Short-term forecasting of passenger demand under on-demand ride services: A spatio-temporal deep learning approach

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