Demystifying Decentralized Fair Models for Federated Machine Learning


Posted on in Presentations

The presentation will unveil the art of incorporating fairness into private federated learning, uncovering key aspects in the design of the predictive system that does not differentiate between majority unprotected users and minority protected users. By the end of the talk, the audience will understand fair federated learning and important KPIs to focus on when designing such a system.


Participants
Sharmistha Chatterjee

Speaker

Senior Manager Data Sciences, Publicis Sapient

Subarna Rana

Speaker

Manager, Data Science, Publicis Sapient

Machine Learning & Artificial Intelligence Privacy Protecting Data & the Supply Chain Ecosystem

big data analytics data security privacy artificial intelligence & machine learning


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