9 citations · 31 across the 31 of their papers we have counts for
4 papers · 1 filter
Distributed Randomized Block Stochastic Gradient Tracking Method
Farzad Yousefian, Jayesh Yevale, Harshal D. Kaushik
We consider distributed optimization over networks where each agent is associated with a smooth and strongly convex local objective function. We assume that the agents only have ac…
Zeroth-order randomized block methods for constrained minimization of expectation-valued Lipschitz continuous functions
Uday V. Shanbhag, Farzad Yousefian
We consider the minimization of an -Lipschitz continuous and expectation-valued function, denoted by and defined as , over a Car…
An Incremental Gradient Method for Optimization Problems with Variational Inequality Constraints
Harshal D. Kaushik, Sepideh Samadi, Farzad Yousefian
We consider minimizing a sum of agent-specific nondifferentiable merely convex functions over the solution set of a variational inequality (VI) problem in that each agent is associ…
Complexity guarantees for an implicit smoothing-enabled method for stochastic MPECs
Shisheng Cui, Uday V. Shanbhag, Farzad Yousefian
Stochastic MPECs have found increasing relevance for modeling a broad range of settings in engineering and statistics. Yet, there seem to be no efficient first/zeroth-order schemes…