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20172026
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math.OC2026

High-Resolution Inertial Dynamics with Time-Rescaled Gradients for Nonsmooth Convex Optimization

Manh Hung Le, Andrea Simonetto

We study nonsmooth convex minimization through a continuous-time dynamical system that can be seen as a high-resolution ODE of Nesterov Accelerated Gradient (NAG) adapted to the no…

math.OC2020

Personalized Demand Response via Shape-Constrained Online Learning

Ana M. Ospina, Andrea Simonetto, Emiliano Dall'Anese

This paper formalizes a demand response task as an optimization problem featuring a known time-varying engineering cost and an unknown (dis)comfort function. Based on this model, t…

math.OC2019

Inexact Online Proximal-gradient Method for Time-varying Convex Optimization

Amirhossein Ajalloeian, Andrea Simonetto, Emiliano Dall'Anese

This paper considers an online proximal-gradient method to track the minimizers of a composite convex function that may continuously evolve over time. The online proximal-gradient…

math.OC2019

On the Convergence of the Inexact Running Krasnosel'skii-Mann Method

Emiliano Dall'Anese, Andrea Simonetto, Andrey Bernstein

This paper leverages a framework based on averaged operators to tackle the problem of tracking fixed points associated with maps that evolve over time. In particular, the paper con…

math.OC2019

Real-time City-scale Ridesharing via Linear Assignment Problems

Andrea Simonetto, Julien Monteil, Claudio Gambella

In this paper, we propose a novel, computational efficient, dynamic ridesharing algorithm. The beneficial computational properties of the algorithm arise from casting the rideshari…

math.OC2019

Dynamic Distribution State Estimation Using Synchrophasor Data

Jianhan Song, Emiliano Dall'Anese, Andrea Simonetto +1

The increasing deployment of distribution-level phasor measurement units (PMUs) calls for dynamic distribution state estimation (DDSE) approaches that tap into high-rate measuremen…