FLea: Addressing Data Scarcity and Label Skew in Federated Learning via Privacy-preserving Feature Augmentation

1 code implementation • 13 Jun 2024 • Tong Xia, Abhirup Ghosh, Xinchi Qiu, Cecilia Mascolo

Federated Learning (FL) enables model development by leveraging data distributed across numerous edge devices without transferring local data to a central server.

Federated Learning Privacy Preserving

FLea: Addressing Data Scarcity and Label Skew in Federated Learning via Privacy-preserving Feature Augmentation

1 code implementation • 4 Dec 2023 • Tong Xia, Abhirup Ghosh, Xinchi Qiu, Cecilia Mascolo

Federated Learning (FL) enables model development by leveraging data distributed across numerous edge devices without transferring local data to a central server.

Federated Learning Privacy Preserving

Cross-device Federated Learning for Mobile Health Diagnostics: A First Study on COVID-19 Detection

no code implementations • 13 Mar 2023 • Tong Xia, Jing Han, Abhirup Ghosh, Cecilia Mascolo

In this paper, we propose FedLoss, a novel cross-device FL framework for health diagnostics.

Federated Learning Privacy Preserving

Continual and Sliding Window Release for Private Empirical Risk Minimization

no code implementations • 7 Mar 2022 • Lauren Watson, Abhirup Ghosh, Benedek Rozemberczki, Rik Sarkar

One version of the algorithm uses the entire data history to improve the model for the recent window.

Heterogeneous Interventions Reduce the Spread of COVID-19 in Simulations on Real Mobility Data

1 code implementation • 14 Aug 2020 • Haotian Wang, Abhirup Ghosh, Jiaxin Ding, Rik Sarkar, Jie Gao

Major interventions have been introduced worldwide to slow down the spread of the SARS-CoV-2 virus.

Social and Information Networks Physics and Society