Convergence of a Distributed Kiefer-Wolfowitz Algorithm
Jean Walrand
TL;DR
This paper proves the convergence of a distributed, asynchronous Kiefer-Wolfowitz algorithm, enabling scalable optimization in distributed systems with potential applications in machine learning and signal processing.
Contribution
It introduces a novel convergence proof for a distributed, asynchronous variant of the Kiefer-Wolfowitz algorithm, expanding its theoretical foundation.
Findings
Proves convergence under certain conditions
Extends Kiefer-Wolfowitz to distributed asynchronous setting
Provides theoretical guarantees for distributed optimization
Abstract
This paper proposes a proof of the convergence of a distributed and asynchronous version of the Kiefer-Wolfowitz algorithm.
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