A scalar-projection federated zeroth-order method for model-free LQR policy learning that reduces per-agent communication from O(d) to O(1) with convergence rate improving in the number of agents.
User-friendly tail bounds for sums of random matrices,
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Scalar Federated Learning for Linear Quadratic Regulator
A scalar-projection federated zeroth-order method for model-free LQR policy learning that reduces per-agent communication from O(d) to O(1) with convergence rate improving in the number of agents.