101 citations · 466 across the 65 of their papers we have counts for
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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 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 min-max optimization with application to demand side management
Ivano Notarnicola, Mauro Franceschelli, Giuseppe Notarstefano
In this paper we consider a distributed optimization scenario in which a set of processors aims at minimizing the maximum of a collection of "separable convex functions" subject to…
A randomized primal distributed algorithm for partitioned and big-data non-convex optimization
Ivano Notarnicola, Giuseppe Notarstefano
In this paper we consider a distributed optimization scenario in which the aggregate objective function to minimize is partitioned, big-data and possibly non-convex. Specifically,…
Distributed Abstract Optimization via Constraints Consensus: Theory and Applications
Giuseppe Notarstefano, Francesco Bullo
Distributed abstract programs are a novel class of distributed optimization problems where (i) the number of variables is much smaller than the number of constraints and (ii) each…