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math.OC2022
Private and Accurate Decentralized Optimization via Encrypted and Structured Functional Perturbation
Yijie Zhou, Shi Pu
We propose a decentralized optimization algorithm that preserves the privacy of agents' cost functions without sacrificing accuracy, termed EFPSN. The algorithm adopts Paillier cry…
math.OC2022
A Compressed Gradient Tracking Method for Decentralized Optimization with Linear Convergence
Yiwei Liao, Zhuorui Li, Kun Huang +1
Communication compression techniques are of growing interests for solving the decentralized optimization problem under limited communication, where the global objective is to minim…