Monotonicity of aggregated gradients holds if and only if the aggregation rule is positively affine; non-affine rules therefore prevent steady convergence and degrade stability.
arXiv preprint arXiv:2006.09365 , year=
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Routing Hijacking forges client profiles to misroute queries in FedRAG, causing failures like incorrect answers and hallucinations, with a trust-aware post-routing defense proposed to mitigate it.
FAR-SIGN achieves adversary-resilient fully asynchronous optimization via signed directional projections and two-timescale correction, with almost-sure convergence to stationary points at rates O(n^{-1/4+ε}) first-order and O(n^{-1/6+ε}) zeroth-order.
citing papers explorer
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Dangerous Liaisons of Convex Learning and Non-Affine Aggregation
Monotonicity of aggregated gradients holds if and only if the aggregation rule is positively affine; non-affine rules therefore prevent steady convergence and degrade stability.
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A Wolf in Sheep's Clothing: Targeted Routing Hijacking in Federated RAG
Routing Hijacking forges client profiles to misroute queries in FedRAG, causing failures like incorrect answers and hallucinations, with a trust-aware post-routing defense proposed to mitigate it.
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Adversary-Robust Learning from Fully Asynchronous Directional Derivative Estimates
FAR-SIGN achieves adversary-resilient fully asynchronous optimization via signed directional projections and two-timescale correction, with almost-sure convergence to stationary points at rates O(n^{-1/4+ε}) first-order and O(n^{-1/6+ε}) zeroth-order.