Zobrazeno 1 - 10
of 119
pro vyhledávání: '"Rinzivillo Salvatore"'
Artificial Intelligence algorithms have now become pervasive in multiple high-stakes domains. However, their internal logic can be obscure to humans. Explainable Artificial Intelligence aims to design tools and techniques to illustrate the prediction
Externí odkaz:
http://arxiv.org/abs/2404.16903
Publikováno v:
2021 IEEE Symposium on Computers and Communications (ISCC)
Explainable AI consists in developing mechanisms allowing for an interaction between decision systems and humans by making the decisions of the formers understandable. This is particularly important in sensitive contexts like in the medical domain. W
Externí odkaz:
http://arxiv.org/abs/2302.03033
Autor:
Serafini, Luciano, Barbosa, Raul, Grosinger, Jasmin, Iocchi, Luca, Napoli, Christian, Rinzivillo, Salvatore, Robin, Jacques, Saffiotti, Alessandro, Scantamburlo, Teresa, Schueller, Peter, Traverso, Paolo, Vazquez-Salceda, Javier
The burgeoning of AI has prompted recommendations that AI techniques should be "human-centered". However, there is no clear definition of what is meant by Human Centered Artificial Intelligence, or for short, HCAI. This paper aims to improve this sit
Externí odkaz:
http://arxiv.org/abs/2112.14480
Autor:
Metta, Carlo, Beretta, Andrea, Guidotti, Riccardo, Yin, Yuan, Gallinari, Patrick, Rinzivillo, Salvatore, Giannotti, Fosca
A key issue in critical contexts such as medical diagnosis is the interpretability of the deep learning models adopted in decision-making systems. Research in eXplainable Artificial Intelligence (XAI) is trying to solve this issue. However, often XAI
Externí odkaz:
http://arxiv.org/abs/2111.11863
Autor:
Bodria, Francesco, Giannotti, Fosca, Guidotti, Riccardo, Naretto, Francesca, Pedreschi, Dino, Rinzivillo, Salvatore
The widespread adoption of black-box models in Artificial Intelligence has enhanced the need for explanation methods to reveal how these obscure models reach specific decisions. Retrieving explanations is fundamental to unveil possible biases and to
Externí odkaz:
http://arxiv.org/abs/2102.13076
Autor:
Miliou, Ioanna, Xiong, Xinyue, Rinzivillo, Salvatore, Zhang, Qian, Rossetti, Giulio, Giannotti, Fosca, Pedreschi, Dino, Vespignani, Alessandro
Increased availability of epidemiological data, novel digital data streams, and the rise of powerful machine learning approaches have generated a surge of research activity on real-time epidemic forecast systems. In this paper, we propose the use of
Externí odkaz:
http://arxiv.org/abs/2012.04651
Autor:
Cintia, Paolo, Pappalardo, Luca, Rinzivillo, Salvatore, Fadda, Daniele, Boschi, Tobia, Giannotti, Fosca, Chiaromonte, Francesca, Bonato, Pietro, Fabbri, Francesco, Penone, Francesco, Savarese, Marcello, Calabrese, Francesco, Guzzetta, Giorgio, Riccardo, Flavia, Marziano, Valentina, Poletti, Piero, Trentini, Filippo, Bella, Antonino, Andrianou, Xanthi, Del Manso, Martina, Fabiani, Massimo, Bellino, Stefania, Boros, Stefano, Urdiales, Alberto Mateo, Vescio, Maria Fenicia, Brusaferro, Silvio, Rezza, Giovanni, Pezzotti, Patrizio, Ajelli, Marco, Merler, Stefano, Vineis, Paolo, Pedreschi, Dino
In 2020, countries affected by the COVID-19 pandemic implemented various non-pharmaceutical interventions to contrast the spread of the virus and its impact on their healthcare systems and economies. Using Italian data at different geographic scales,
Externí odkaz:
http://arxiv.org/abs/2006.03141
Autor:
Bonato, Pietro, Cintia, Paolo, Fabbri, Francesco, Fadda, Daniele, Giannotti, Fosca, Lopalco, Pier Luigi, Mazzilli, Sara, Nanni, Mirco, Pappalardo, Luca, Pedreschi, Dino, Penone, Francesco, Rinzivillo, Salvatore, Rossetti, Giulio, Savarese, Marcello, Tavoschi, Lara
Understanding collective mobility patterns is crucial to plan the restart of production and economic activities, which are currently put in stand-by to fight the diffusion of the epidemics. In this report, we use mobile phone data to infer the moveme
Externí odkaz:
http://arxiv.org/abs/2004.11278
Autor:
Nanni, Mirco, Andrienko, Gennady, Barabási, Albert-László, Boldrini, Chiara, Bonchi, Francesco, Cattuto, Ciro, Chiaromonte, Francesca, Comandé, Giovanni, Conti, Marco, Coté, Mark, Dignum, Frank, Dignum, Virginia, Domingo-Ferrer, Josep, Ferragina, Paolo, Giannotti, Fosca, Guidotti, Riccardo, Helbing, Dirk, Kaski, Kimmo, Kertesz, Janos, Lehmann, Sune, Lepri, Bruno, Lukowicz, Paul, Matwin, Stan, Jiménez, David Megías, Monreale, Anna, Morik, Katharina, Oliver, Nuria, Passarella, Andrea, Passerini, Andrea, Pedreschi, Dino, Pentland, Alex, Pianesi, Fabio, Pratesi, Francesca, Rinzivillo, Salvatore, Ruggieri, Salvatore, Siebes, Arno, Trasarti, Roberto, Hoven, Jeroen van den, Vespignani, Alessandro
Publikováno v:
Transactions on Data Privacy 13(1): 61-66 (2020), http://www.tdp.cat/issues16/abs.a389a20.php
The rapid dynamics of COVID-19 calls for quick and effective tracking of virus transmission chains and early detection of outbreaks, especially in the phase 2 of the pandemic, when lockdown and other restriction measures are progressively withdrawn,
Externí odkaz:
http://arxiv.org/abs/2004.05222
Autor:
Rossetti, Giulio, Milli, Letizia, Rinzivillo, Salvatore, Sirbu, Alina, Giannotti, Fosca, Pedreschi, Dino
Publikováno v:
International Journal of Data Science and Analytics, 2018
Nowadays the analysis of dynamics of and on networks represents a hot topic in the Social Network Analysis playground. To support students, teachers, developers and researchers in this work we introduce a novel framework, namely NDlib, an environment
Externí odkaz:
http://arxiv.org/abs/1801.05854