Distributed subgradient methods and quantization effects

@article{Nedic2008DistributedSM,
  title={Distributed subgradient methods and quantization effects},
  author={Angelia Nedic and Alexander Olshevsky and Asuman E. Ozdaglar and John N. Tsitsiklis},
  journal={2008 47th IEEE Conference on Decision and Control},
  year={2008},
  pages={4177-4184}
}
We consider a convex unconstrained optimization problem that arises in a network of agents whose goal is to cooperatively optimize the sum of the individual agent objective functions through local computations and communications. For this problem, we use averaging algorithms to develop distributed subgradient methods that can operate over a time-varying topology. Our focus is on the convergence rate of these methods and the degradation in performance when only quantized information is available… CONTINUE READING

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