Search Results for author:
Found 3 papers, 0 papers with code
A Framework for Incentivized Collaborative Learning
Collaborations among various entities, such as companies, research labs, AI agents, and edge devices, have become increasingly crucial for achieving machine learning tasks that cannot be accomplished by a single entity alone.
PI-FL: Personalized and Incentivized Federated Learning
Personalized FL has been widely used to cater to heterogeneity challenges with non-IID data.
Towards cost-effective and resource-aware aggregation at Edge for Federated Learning
Federated Learning (FL) is a machine learning approach that addresses privacy and data transfer costs by computing data at the source.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
