5 papers
A stochastic perturbed augmented Lagrangian method for smooth convex constrained minimization
Nitesh Kumar Singh, Ion Necoara
This paper considers smooth convex optimization problems with many functional constraints. To solve this general class of problems we propose a new stochastic perturbed augmented L…
Stochastic halfspace approximation method for convex optimization with nonsmooth functional constraints
Nitesh Kumar Singh, Ion Necoara
In this work, we consider convex optimization problems with smooth objective function and nonsmooth functional constraints. We propose a new stochastic gradient algorithm, called S…
A stochastic moving ball approximation method for smooth convex constrained minimization
Nitesh Kumar Singh, Ion Necoara
In this paper, we consider constrained optimization problems with convex, smooth objective and constraints. We propose a new stochastic gradient algorithm, called the Stochastic Mo…
Mini-batch stochastic subgradient for functional constrained optimization
Nitesh Kumar Singh, Ion Necoara, Vyacheslav Kungurtsev
In this paper we consider finite sum composite convex optimization problems with many functional constraints. The objective function is expressed as a finite sum of two terms, one…
Stochastic subgradient for composite optimization with functional constraints
Ion Necoara, Nitesh Kumar Singh
In this paper we consider convex optimization problems with stochastic composite objective function subject to (possibly) infinite intersection of constraints. The objective functi…