IEEE22d
Robust Asymmetric Heterogeneous Federated Learning with Corrupted Clients
To address these issues, this paper introduces a novel Robust Asymmetric Heterogeneous Federated Learning (RAHFL) framework. We propose a Diversity-enhanced supervised Contrastive Learning technique ...
IEEE15d
Federated Contrastive Learning for Cross-Domain Recommendation
Persistent Link: https://ieeexplore.ieee.org/servlet/opac?punumber=4629386 ...
InfoWorld12d
Federated learning: The killer use case for generative AI
As enterprises struggle to balance AI capabilities against data privacy concerns, federated learning provides the best of ...
Nature6d
Federated Learning and Privacy Preservation
Federated Learning (FL) is an innovative approach to machine learning that allows multiple parties to collaboratively train models without sharing their raw data. This method has gained traction ...
Wall Street Journal6d
Federated Hermes Corporate Bond Fund;A
The Fund seeks to provide as high a level of current income as is consistent with the preservation of capital. The Fund invests primarily in a diversified portfolio of investment-grade corporate ...
The New York Times1d
The Learning Network
Compiled by Jeremy Engle Do you celebrate the Lunar New Year? How? By The Learning Network Choose three to five works of art or culture to group in some way, then tell us why we should — or ...
GitHub13d
federated-learning
FEDML - The unified and scalable ML library for large-scale distributed training, model serving, and federated learning. FEDML Launch, a cross-cloud scheduler, further enables running any AI jobs on ...