ARGFree is the first gradient-free method for aggregative cooperative optimization, converging in expectation to an approximate solution via randomized finite differences and tracking, with a momentum-enhanced variant for high dimensions.
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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.
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Model-Free Aggregative Cooperative Optimization via Randomized Gradient-Free Minimization and Exploration Momentum
ARGFree is the first gradient-free method for aggregative cooperative optimization, converging in expectation to an approximate solution via randomized finite differences and tracking, with a momentum-enhanced variant for high dimensions.
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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.