14 citations · 45 across the 7 of their papers we have counts for
4 papers · 1 filter
FedDefender: Backdoor Attack Defense in Federated Learning
Waris Gill, Ali Anwar, Muhammad Ali Gulzar
Federated Learning (FL) is a privacy-preserving distributed machine learning technique that enables individual clients (e.g., user participants, edge devices, or organizations) to…
A Framework for Incentivized Collaborative Learning
Xinran Wang, Qi Le, Ahmad Faraz Khan +2
Collaborations among various entities, such as companies, research labs, AI agents, and edge devices, have become increasingly crucial for achieving machine learning tasks that can…
IP-FL: Incentivized and Personalized Federated Learning
Ahmad Faraz Khan, Xinran Wang, Qi Le +7
Existing incentive solutions for traditional Federated Learning (FL) focus on individual contributions to a single global objective, neglecting the nuances of clustered personaliza…
FedDebug: Systematic Debugging for Federated Learning Applications
Waris Gill, Ali Anwar, Muhammad Ali Gulzar
In Federated Learning (FL), clients independently train local models and share them with a central aggregator to build a global model. Impermissibility to access clients' data and…