Residual-weighted randomized Jacobi with ℓ=2 selection sharpens one-step convergence by exactly the inverse participation ratio ν² of the residual and extends the analysis to asynchronous execution where the same quantity controls both progress and allowable delay.
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Asynchronous execution yields 2.9x-16.9x speedups across Jacobi, value iteration, and SCF methods; Anderson acceleration succeeds only under evaluation-level perturbation, not iterate-level corruption.
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Residual-Weighted Randomized Jacobi: Sharpened Bounds via Residual Concentration and Asynchronous Extension
Residual-weighted randomized Jacobi with ℓ=2 selection sharpens one-step convergence by exactly the inverse participation ratio ν² of the residual and extends the analysis to asynchronous execution where the same quantity controls both progress and allowable delay.