FedOUI downweights federated clients whose activation patterns on a probe batch deviate from the round-wise OUI distribution, yielding gains under strong non-IID and noisy conditions on CIFAR-10.
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2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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cs.LG 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
OUI provides an activation-based observable that anticipates training regimes across supervised learning, reinforcement learning, and control tasks before convergence occurs.
citing papers explorer
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FedOUI: OUI-Guided Client Weighting for Federated Aggregation
FedOUI downweights federated clients whose activation patterns on a probe batch deviate from the round-wise OUI distribution, yielding gains under strong non-IID and noisy conditions on CIFAR-10.
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OUI as a Structural Observable: Towards an Activation-Centric View of Neural Network Training
OUI provides an activation-based observable that anticipates training regimes across supervised learning, reinforcement learning, and control tasks before convergence occurs.