4 papers
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…
A Method with Convergence Rates for Optimization Problems with Variational Inequality Constraints
Harshal D. Kaushik, Farzad Yousefian
We consider a class of optimization problems with Cartesian variational inequality (CVI) constraints, where the objective function is convex and the CVI is associated with a monoto…
An Incremental Gradient Method for Large-scale Distributed Nonlinearly Constrained Optimization
Harshal D. Kaushik, Farzad Yousefian
Motivated by applications arising from sensor networks and machine learning, we consider the problem of minimizing a finite sum of nondifferentiable convex functions where each com…
A Randomized Block Coordinate Iterative Regularized Gradient Method for High-dimensional Ill-posed Convex Optimization
Harshal Kaushik, Farzad Yousefian
Motivated by high-dimensional nonlinear optimization problems as well as ill-posed optimization problems arising in image processing, we consider a bilevel optimization model where…