EXTRA: An Exact First-Order Algorithm for Decentralized Consensus Optimization

Recently, there has been growing interest in solving consensus optimization problems in a multiagent network. In this paper, we develop a decentralized algorithm for the consensus optimization problem $\mathrm{minimize}_{x\in\mathbb{R}^p}~\bar{f}(x)=\frac{1}{n}\sum_{i=1}^n f_i(x),$ which is defined over a connected network of $n$ agents, where each function $f_i$ is held privately by agent $i$ and encodes the agent's data and objective. All the agents shall collaboratively find the minimizer while each agent can only communicate with its neighbors. Such a computation scheme avoids a data fusion center or long-distance communication and offers better load balance to the network. This paper proposes a novel…

• NS
  National Science Foundation

  Awards: 0748839, 1317602
• NN
  National Natural Science Foundation of China

  Award: 61004137
• CS
  China Scholarship Council
• MO
  Ministry of Industry and Information Technology of the People's Republic of China