5 citations · 5 across the 3 of their papers we have counts for
3 papers
Exploring Machine Learning Models for Federated Learning: A Review of Approaches, Performance, and Limitations
Elaheh Jafarigol, Theodore Trafalis, Talayeh Razzaghi +1
In the growing world of artificial intelligence, federated learning is a distributed learning framework enhanced to preserve the privacy of individuals' data. Federated learning la…
The Paradox of Noise: An Empirical Study of Noise-Infusion Mechanisms to Improve Generalization, Stability, and Privacy in Federated Learning
Elaheh Jafarigol, Theodore Trafalis
In a data-centric era, concerns regarding privacy and ethical data handling grow as machine learning relies more on personal information. This empirical study investigates the priv…
Religious Affiliation in the Twenty-First Century: A Machine Learning Perspective on the World Value Survey
Elaheh Jafarigol, William Keely, Tess Hartog +3
This paper is a quantitative analysis of the data collected globally by the World Value Survey. The data is used to study the trajectories of change in individuals' religious belie…