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.
Signsgd with federated defense: Harnessing adversarial attacks through gradient sign decoding
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.LG 2verdicts
UNVERDICTED 2roles
background 1polarities
background 1representative citing papers
RESIST achieves algorithmic and statistical convergence guarantees for strongly convex, PL, and nonconvex ERM under MITM attacks via multistep consensus gradient descent plus robust screening.
citing papers explorer
-
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.
-
RESIST: Resilient Decentralized Learning Using Consensus Gradient Descent
RESIST achieves algorithmic and statistical convergence guarantees for strongly convex, PL, and nonconvex ERM under MITM attacks via multistep consensus gradient descent plus robust screening.