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math.OC2024
Achieving Near-Optimal Convergence for Distributed Minimax Optimization with Adaptive Stepsizes
Yan Huang, Xiang Li, Yipeng Shen +2
In this paper, we show that applying adaptive methods directly to distributed minimax problems can result in non-convergence due to inconsistency in locally computed adaptive steps…
cs.LG2024
PrivSGP-VR: Differentially Private Variance-Reduced Stochastic Gradient Push with Tight Utility Bounds
Zehan Zhu, Yan Huang, Xin Wang +1
In this paper, we propose a differentially private decentralized learning method (termed PrivSGP-VR) which employs stochastic gradient push with variance reduction and guarantees $…