Krylov subspace acceleration for first-order methods on convex QPs outperforms Anderson acceleration in iterations and often runtime by avoiding ill-conditioning during slow convergence.
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The paper provides stability criteria for multi-agent systems with heterogeneous model predictive game controllers and quantifies sensitivity of equilibria to objective misspecifications.
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Krylov Subspace Acceleration for First-Order Splitting Methods in Convex Quadratic Programming
Krylov subspace acceleration for first-order methods on convex QPs outperforms Anderson acceleration in iterations and often runtime by avoiding ill-conditioning during slow convergence.
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Stability and Sensitivity Analysis for Objective Misspecifications Among Model Predictive Game Controllers
The paper provides stability criteria for multi-agent systems with heterogeneous model predictive game controllers and quantifies sensitivity of equilibria to objective misspecifications.