Proposes single-stage and two-stage distributed implicit zeroth-order gradient tracking methods for stochastic MPECs over networks that achieve best-known complexity bounds for centralized nonsmooth nonconvex stochastic optimization under uniqueness and Lipschitz assumptions.
Goldstein, Optimization of Lipschitz continuous functions, Mathematical Programming, 13 (1977), pp
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On the Resolution of Stochastic MPECs over Networks: Distributed Implicit Zeroth-Order Gradient Tracking Methods
Proposes single-stage and two-stage distributed implicit zeroth-order gradient tracking methods for stochastic MPECs over networks that achieve best-known complexity bounds for centralized nonsmooth nonconvex stochastic optimization under uniqueness and Lipschitz assumptions.