101 citations · 174 across the 22 of their papers we have counts for
7 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 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…
Distributed Partitioned Big-Data Optimization via Asynchronous Dual Decomposition
Ivano Notarnicola, Ruggero Carli, Giuseppe Notarstefano
In this paper we consider a novel partitioned framework for distributed optimization in peer-to-peer networks. In several important applications the agents of a network have to sol…
Distributed Big-Data Optimization via Block-Iterative Convexification and Averaging
Ivano Notarnicola, Ying Sun, Gesualdo Scutari +1
In this paper, we study distributed big-data nonconvex optimization in multi-agent networks. We consider the (constrained) minimization of the sum of a smooth (possibly) nonconvex…
A Duality-Based Approach for Distributed Optimization with Coupling Constraints
Ivano Notarnicola, Giuseppe Notarstefano
In this paper we consider a distributed optimization scenario in which a set of agents has to solve a convex optimization problem with separable cost function, local constraint set…