A collaborative approach to training AI models can yield better results, but it requires finding partners with data that ...
FedCare delivers the first visual pipeline that pinpoints, classifies and mitigates FL failures in real time, cutting ...
FPMCO decomposes multi-constraint RL into KL-projection sub-problems, achieving higher reward with lower computing than second-order rivals on the new SCIG robotics benchmark.
The integration of artificial intelligence (AI) with imaging has emerged as a transformative force in the field of oral oncology. Oral cancer remains a ...
Background: Multi-center Federated Learning (FL) has played a significant role in disease prediction, offering a feasible solution to the challenges of cross-institutional collaboration. However, the ...
At this year’s Credit Scoring and Credit Control Conference in Edinburgh, colleagues Ben Archer and Peter Szocs presented on a topic gaining significant attention: how federated learning can support ...
It supports client-wise data partitioning and federated learning with feature selection for high-dimensional tabular datasets like IoT-IDS or spam classification. spambase-fed-bfa.ipynb Federated BFA ...
Vikram Gupta is Chief Product Officer, SVP & GM of the IoT Processor Business Division at Synaptics, a leading EdgeAI semiconductor company. In my previous articles, I explored how the rapid growth of ...
Abstract: In the Internet of Vehicles (IoV), developing accurate road information models is essential for analyzing perception data gathered from multiple vehicles. However, traditional centralized ...
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