Aug 22, 2024 · We present KAFÈ, a novel yet simple aggregation solution designed to address non-IID-ness by introducing Kernel Aggregation for FEderated Learning.
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The convergence and generalization abilities of federated learning (FL) models encounter significant obstacles when confronted with non-independent.
Sep 1, 2024 · For this paper, we studied the time evolution of a system of coagulating particles under a generalized electrorheological (ER) kernel with real ...
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What is aggregation in federated learning?
What is secure aggregation in federated learning?
The performance of Federated Learning (FL) hinges on the effectiveness of utilizing knowledge from distributed datasets. Traditional FL methods adopt an ...
Missing: KAFÈ: | Show results with:KAFÈ:
Although CAFE comes with theoretical recovery guarantees, the underlying premise is that the clients will upload true (correct) gradients for aggregation.
Missing: KAFÈ: | Show results with:KAFÈ:
Apr 29, 2024 · We introduce FedAF, a novel aggregation-free FL algorithm. In this framework, clients collaboratively learn condensed data by leveraging peer knowledge.
Missing: KAFÈ: | Show results with:KAFÈ:
Feb 3, 2022 · Completion Certificate for Python per la Data Science · Explore topics.
In this work, we consider training a deep neural network in the Federated Learning model, using distributed gradient descent across user-held training data on ...
[PDF] Federated Learning of Large Models at the Edge via Principal Sub-Model ...
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Limited compute and communication capabilities of edge users create a significant bottleneck for federated learning (FL) of large models.
Comparing to existing data leakage attacks, CAFE demonstrates the ability to perform large-batch data leakage attack with high data recovery quality.