Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Andrea Camisa"'
Autor:
Andrea Camisa, Giovanni Montanari, Andrea Testa, Luigi Falzetti, Sofia Avnet, Nicola Baldini, Giuseppe Notarstefano
Publikováno v:
IEEE Access, Vol 12, Pp 65310-65322 (2024)
Convolutional Neural Networks are being increasingly applied to the detection of anomalies in Computed Tomographies (CTs). The goal of this paper is to implement an automated Computer-Aided Detection (CADe) system for spinal lesions using CTs and Con
Externí odkaz:
https://doaj.org/article/df01d6d7df2c457abc5cbd851ce04bb0
Publikováno v:
IEEE Transactions on Automatic Control. 68:3736-3743
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::70122f431d488ded4db9827c11c16515
https://doi.org/10.1109/tac.2022.3196627
https://doi.org/10.1109/tac.2022.3196627
Publikováno v:
2022 IEEE 61st Conference on Decision and Control (CDC).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::eef025892a637e509f92332d7f4ccf88
https://doi.org/10.1109/cdc51059.2022.9992584
https://doi.org/10.1109/cdc51059.2022.9992584
Publikováno v:
IEEE Control Systems Letters
In this letter we consider a distributed stochastic optimization framework in which agents in a network aim to cooperatively learn an optimal network-wide policy. The goal is to compute local functions to minimize the expected value of a given cost,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a76d1b573a7fa327ad13bbdab54db064
Autor:
Giuseppe Notarstefano, Andrea Camisa
This article deals with distributed control of microgrids composed of storages, generators, renewable energy sources, and critical and controllable loads. We consider a stochastic formulation of the optimal control problem associated with the microgr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::16de05aa218176c91e0d4c472a9976b5
https://hdl.handle.net/11585/896747
https://hdl.handle.net/11585/896747
In this paper, we consider a large-scale instance of the classical Pickup-and-Delivery Vehicle Routing Problem (PDVRP) that must be solved by a network of mobile cooperating robots. Robots must self-coordinate and self-allocate a set of pickup/delive
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::567d08c113cff412d43f00acb90f172c
Distributed constraint-coupled optimization via primal decomposition over random time-varying graphs
Publikováno v:
Automatica
The paper addresses large-scale, convex optimization problems that need to be solved in a distributed way by agents communicating according to a random time-varying graph. Specifically, the goal of the network is to minimize the sum of local costs, w
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::21496eed7c7573865752e18ec6407dbc
Publikováno v:
2019 IEEE 58th Conference on Decision and Control (CDC)
CDC
CDC
In this paper, we consider a network of processors that want to cooperatively solve a large-scale, convex optimization problem. Each processor has knowledge of a local cost function that depends only on a local variable. The goal is to minimize the s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1456772116e4dbf5ab95957705315fa8
Publikováno v:
IFAC-Papers
In this paper we introduce disropt, a Python package for distributed optimization over networks. We focus on cooperative set-ups in which an optimization problem must be solved by peer-to-peer processors (without central coordinators) that have acces
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::370f5bac4b0b678db5eef6fdd5755037
Publikováno v:
IFAC-Papers
In this paper, we consider a multi-objective optimization problem over networks in which agents aim to maximize their own objective function, while satisfying both local and coupling constraints. This set up includes, e.g., the computation of optimal
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5bb36a628ee70c739f4a2f7a60ef6b18
http://hdl.handle.net/11585/822585
http://hdl.handle.net/11585/822585