2 citations · 4 across the 10 of their papers we have counts for
3 papers · 1 filter
Privacy Drift: Evolving Privacy Concerns in Incremental Learning
Sayyed Farid Ahamed, Soumya Banerjee, Sandip Roy +6
In the evolving landscape of machine learning (ML), Federated Learning (FL) presents a paradigm shift towards decentralized model training while preserving user data privacy. This…
Accuracy-Privacy Trade-off in the Mitigation of Membership Inference Attack in Federated Learning
Sayyed Farid Ahamed, Soumya Banerjee, Sandip Roy +7
Over the last few years, federated learning (FL) has emerged as a prominent method in machine learning, emphasizing privacy preservation by allowing multiple clients to collaborati…
Anomaly Detection via Federated Learning
Marc Vucovich, Amogh Tarcar, Penjo Rebelo +11
Machine learning has helped advance the field of anomaly detection by incorporating classifiers and autoencoders to decipher between normal and anomalous behavior. Additionally, fe…