Online distributed optimization with stochastic gradients: high probability bound of regrets

• Published in: Control theory and technology Vol. 22; no. 3; pp. 419 - 430
• Main Authors: Yang, Yuchen, Lu, Kaihong, Wang, Long
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.08.2024; Springer Nature B.V; Center for Systems and Control,College of Engineering,Peking University,Beijing 100871,China%College of Electrical Engineering and Automation,Shandong University of Science and Technology,Qingdao 266590,Shandong,China
• Subjects: Algorithms; Complexity; Computational Intelligence; Control; Control and Systems Theory; Convexity; Engineering; Graph theory; Mechatronics; Optimization; Probability theory; Research Article; Robotics; Systems Theory; Online optimization; Distributed optimization; High probability; Stochastic gradient

In this paper, the problem of online distributed optimization subject to a convex set is studied via a network of agents. Each agent only has access to a noisy gradient of its own objective function, and can communicate with its neighbors via a network. To handle this problem, an online distributed...