Abstract
The Gauss-Newton algorithm is a popular and efficient centralized method for
solving non-linear least squares problems. In this paper, we propose a multi-agent
distributed version of this algorithm, named Gossip-based Gauss-Newton (GGN) algorithm,
which can be applied in general problems with non-convex objectives. Furthermore, we
analyze and present sufficient conditions for its convergence and show numerically that the
GGN algorithm achieves performance comparable to the centralized algorithm, with graceful
degradation in case of network failures. More importantly, the GGN algorithm provides
significant performance gains compared to other distributed first order methods.
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