Distributed optimization is a research area that focuses on developing algorithms and techniques for solving optimization problems in a decentralized manner. In distributed optimization, the optimization problem is divided into smaller subproblems that are solved by individual agents or nodes in a distributed network. These agents communicate and collaborate with each other to collectively find the optimal solution to the overall optimization problem. Distributed optimization has applications in various fields such as machine learning, signal processing, control systems, and telecommunications. It allows for efficient and scalable optimization in large-scale systems where centralized optimization may be impractical or not feasible.