We generalize the primal-dual hybrid gradient (PDHG) algorithm proposed by Zhu and
Chan in An Efficient Primal-Dual Hybrid Gradient Algorithm for Total Variation Image …

This paper deals with load control in a multiple-residence setup. The utility company adopts
a cost function representing the cost of providing energy to end-users. Each residential end …

This paper addresses the design and analysis of feedback-based online algorithms to
control systems or networked systems based on performance objectives and engineering …

We present a unified convergence framework for approximate subgradient methods that
covers various stepsize rules (including both diminishing and nonvanishing stepsizes) …

This paper considers future distribution networks featuring inverter-interfaced photovoltaic
(PV) systems, and addresses the synthesis of feedback controllers that seek real-and …

In this paper we establish the convergence of a general primal–dual method for nonsmooth
convex optimization problems whose structure is typical in the imaging framework, as, for …

Minimization problems often occur in modeling phenomena dealing with real-life
applications that nowadays handle large-scale data and require real-time solutions. For …

One of the prime goals of statistical estimation theory is the development of performance
bounds when estimating parameters of interest in a given model, as well as constructing …

An important aspect of estimation theory is characterizing the best achievable performance
in a given estimation problem, as well as determining estimators that achieve the optimal …

In this paper, we consider a generic inexact subgradient algorithm to solve a
nondifferentiable quasi-convex constrained optimization problem. The inexactness stems …