Privacy Preservation in Distributed Subgradient Optimization Algorithms
Privacy Preservation in Distributed Subgradient Optimization Algorithms
In this paper, some privacy-preserving features for distributed subgradient optimization algorithms are considered. Most of the existing distributed algorithms focus mainly on the algorithm design and convergence analysis, but not the protection of agents' privacy. Privacy is becoming an increasingly important issue in applications involving sensitive information. In this paper, …