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math.OC2026
Multiple Approximate-Response Agents (MARA): Fast Near-Optimal Primal Recovery for Distributed Optimization
Tetiana Parshakova, Yicheng Bai, Garrett van Ryzin +1
Dual methods are useful for distributed optimization because they allow agent-level subproblems to be solved in parallel. However, achieving primal feasibility with dual methods is…
math.OC2025
Optimization Algorithm Design via Electric Circuits
Stephen P. Boyd, Tetiana Parshakova, Ernest K. Ryu +1
We present a novel methodology for convex optimization algorithm design using ideas from electric RLC circuits. Given an optimization problem, the first stage of the methodology is…