101 citations · 466 across the 65 of their papers we have counts for
13 papers · 1 filter
Distributed Submodular Minimization over Networks: a Greedy Column Generation Approach
Andrea Testa, Ivano Notarnicola, Giuseppe Notarstefano
Submodular optimization is a special class of combinatorial optimization arising in several machine learning problems, but also in cooperative control of complex systems. In this p…
A Primal Decomposition Method with Suboptimality Bounds for Distributed Mixed-Integer Linear Programming
Andrea Camisa, Ivano Notarnicola, Giuseppe Notarstefano
In this paper we deal with a network of agents seeking to solve in a distributed way Mixed-Integer Linear Programs (MILPs) with a coupling constraint (modeling a limited shared res…
Distributed Big-Data Optimization via Block-wise Gradient Tracking
Ivano Notarnicola, Ying Sun, Gesualdo Scutari +1
We study distributed big-data nonconvex optimization in multi-agent networks. We consider the (constrained) minimization of the sum of a smooth (possibly) nonconvex function, i.e.,…
Distributed Learning from Interactions in Social Networks
Francesco Sasso, Angelo Coluccia, Giuseppe Notarstefano
We consider a network scenario in which agents can evaluate each other according to a score graph that models some interactions. The goal is to design a distributed protocol, run b…
A Distributed Asynchronous Method of Multipliers for Constrained Nonconvex Optimization
Francesco Farina, Andrea Garulli, Antonio Giannitrapani +1
This paper presents a fully asynchronous and distributed approach for tackling optimization problems in which both the objective function and the constraints may be nonconvex. In t…
Distributed Big-Data Optimization via Block Communications
Ivano Notarnicola, Ying Sun, Gesualdo Scutari +1
We study distributed multi-agent large-scale optimization problems, wherein the cost function is composed of a smooth possibly nonconvex sum-utility plus a DC (Difference-of-Convex…