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Catalogo Ricerca: [5204] Home page macrotipologia

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1 Contributo su Rivista 2807
- 1.1 Articolo in rivista 2585
- 1.2 Recensione in rivista 138
- 1.3 Scheda bibliografica 5
- 1.4 Nota a sentenza 14
- 1.5 Abstract in rivista 62
- 1.6 Traduzione in rivista 3

2 Contributo in Volume 899

3 Libro 114
- 3.1 Monografia o trattato scientifico 100
- 3.2 Concordanza 0
- 3.3 Indice 1
- 3.4 Bibliografia 0
- 3.5 Edizione critica 1
- 3.6 Pubblicazione di fonti inedite 5
- 3.7 Commento scientifico 1
- 3.8 Traduzione di libro 6

4 Contributo in Atti di Convegno (Proceeding) 1189
- 4.1 Contributo in Atti di convegno 1069
- 4.2 Abstract in Atti di convegno 91
- 4.3 Poster 29

5 Altro 86
- 5.01 Composizione 3
- 5.02 Disegno 0
- 5.03 Design 0
- 5.04 Performance 0
- 5.05 Esposizione 0
- 5.06 Mostra 2
- 5.07 Manufatto 0
- 5.08 Prototipo d'arte e relativi progetti 0
- 5.09 Cartografia 0
- 5.10 Banca dati 2
- 5.11 Software 3
- 5.12 Working paper 29
- 5.13 Progetto architettonico 0
- 5.14 Rapporto tecnico / Rapporto di ricerca 14
- 5.15 Altro 33

6 Brevetti 6
- 6.1 Brevetto 6

7 Curatele 103
- 7.1 Curatela 103

Prodotti recenti

An LMI-based controller for the glucose-insulin system

Exogenous insulin administration is the standard way to regulate hyperglycemia in diabetic patients and, in the recent decades, the challenging task to design an artificial pancreas has been addressed with the aim to synthesize a closed-loop control law by means of sampled glucose measurements. Model-based control law allow to explicitly exploit the glucose-insulin mathematical model, but need to cope with different sources of uncertainties and disturbances affecting the system. The present n...

Neural network training as an optimal control problem: An augmented Lagrangian approach

Training of neural networks amounts to nonconvex optimization problems that are typically solved by using backpropagation and (variants of) stochastic gradient descent. In this work, we propose an alternative approach by viewing the training task as a nonlinear optimal control problem. Under this lens, backpropagation amounts to the sequential approach (single shooting) to optimal control, where the states variables have been eliminated. It is well known that single shooting may lead to ill-c...

Multi-agent structured optimization over message-passing architectures with bounded communication delays

We consider the problem of solving structured convex optimization problems over a network of agents with communication delays. It is assumed that each agent performs its local updates using possibly outdated information from its neighbors under the assumption that the delay with respect to each neighbor is bounded but otherwise arbitrary. The private objective of each agent is represented by the sum of two possibly nonsmooth functions one of which is composed with a linear mapping. The global...

SPIRAL: a superlinearly convergent incremental proximal algorithm for nonconvex finite sum minimization

We introduce SPIRAL, a SuPerlinearly convergent Incremental pRoximal ALgorithm, for solving nonconvex regularized finite sum problems under a relative smoothness assumption. Each iteration of SPIRAL consists of an inner and an outer loop. It combines incremental gradient updates with a linesearch that has the remarkable property of never being triggered asymptotically, leading to superlinear convergence under mild assumptions at the limit point. Simulation results with L-BFGS directions on di...

Primal-dual algorithms for multi-agent structured optimization over message-passing architectures with bounded communication delays

We consider algorithms for solving structured convex optimization problems over a network of agents with communication delays. It is assumed that each agent performs its local updates using possibly outdated information from its neighbours under the assumption that the delay with respect to each neighbour is bounded but otherwise arbitrary. The private objective of each agent is represented by the sum of two possibly nonsmooth functions one of which is composed with a linear mapping. The glob...

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