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math.OC2023
Jointly Improving the Sample and Communication Complexities in Decentralized Stochastic Minimax Optimization
Xuan Zhang, Gabriel Mancino-Ball, Necdet Serhat Aybat +1
We propose a novel single-loop decentralized algorithm called DGDA-VR for solving the stochastic nonconvex strongly-concave minimax problem over a connected network of agents.…
math.OC2023
High Probability and Risk-Averse Guarantees for a Stochastic Accelerated Primal-Dual Method
Yassine Laguel, Necdet Serhat Aybat, Mert Gürbüzbalaban
We consider stochastic strongly-convex-strongly-concave (SCSC) saddle point (SP) problems which frequently arise in applications ranging from distributionally robust learning to ga…