@inproceedings{ce93a2c9e1f9432cab0706c34dc33c1a,
title = "Data Obfuscation Scenarios for Batch ELM in Federated Learning Applications",
abstract = "The batch formulation of the Extreme Learning Machines (ELM) method fits well with federated learning scenarios. This paper proposes and investigates the strategies for data obfuscation that can be used in combination with ELM to create a secure distributed learning environment. Results show that the model allows for significant levels of added noise with minimal impact on its predictive performance; enabling secure federated learning in tasks that can benefit from it.",
keywords = "Batch processing, Extreme Learning Machine, Federated learning",
author = "Anton Akusok and Leonardo Espinosa-Leal and Tamirat Atsemegiorgis and Kaj-Mikael Bj{\"o}rk",
year = "2024",
doi = "10.1007/978-3-031-61905-2\_32",
language = "English",
isbn = "978-3-031-61904-5",
volume = "2",
series = "Lecture Notes in Networks and Systems",
publisher = "Springer",
pages = "329--338",
editor = "Auer, \{Michael E.\} and Reinhard Langmann and Dominik May and Kim Roos",
booktitle = "Smart Technologies for a Sustainable Future",
address = "Germany",
note = "21st International Conference on Smart Technologies \& Education (STE-2024) ; Conference date: 06-03-2024 Through 08-03-2024",
}