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[18]
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Arnaud Nguembang Fadja, Fabrizio Riguzzi, and Evelina Lamma.
Learning hierarchical probabilistic logic programs.
Machine Learning, 110(7):1637--1693, © Springer,
2021.
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[17]
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Damiano Azzolini, Fabrizio Riguzzi, and Evelina Lamma.
A semantics for hybrid probabilistic logic programs with function
symbols.
Artificial Intelligence, 294:103452, © Elsevier,
2021.
The final publication is available at Elsevier via
https://doi.org/10.1016/j.artint.2021.103452.
[ bib |
DOI |
.pdf ]
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[16]
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Enzo Losi, Mauro Venturini, Lucrezia Manservigi, Giuseppe Fabio Ceschini,
Giovanni Bechini, Giuseppe Cota, and Fabrizio Riguzzi.
Structured methodology for clustering gas turbine transients by means
of multi-variate time series.
Journal of Engineering for Gas Turbines and Power,
143(3):031014--1 (13 pages), 2021.
[ bib |
DOI ]
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[15]
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Fabrizio Riguzzi, Elena Bellodi, Riccardo Zese, Marco Alberti, and Evelina
Lamma.
Probabilistic inductive constraint logic.
Machine Learning, 110:723--754, 2021.
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DOI |
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[14]
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Michele Fraccaroli, Evelina Lamma, and Fabrizio Riguzzi.
Automatic setting of DNN hyper-parameters by mixing Bayesian
Optimization and tuning rules.
In Giuseppe Nicosia, Varun Ojha, Emanuele La Malfa, Giorgio Jansen,
Vincenzo Sciacca, Panos Pardalos, Giovanni Giuffrida, and Renato Umeton,
editors, Machine Learning, Optimization, and Data Science, 6th
International Conference, LOD 2020, Siena, Italy, July 19–23, 2020, Revised
Selected Papers, Part I, volume 12565 of Lecture Notes in Computer
Science, pages 477--488, Cham, 2020. © Springer, Springer
International Publishing.
The final publication is available at Springer via
https://link.springer.com/chapter/10.1007/978-3-030-64583-0_43.
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[13]
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Marco Alberti, Marco Gavanelli, Evelina Lamma, Fabrizio Riguzzi, Ken Satoh, and
Riccardo Zese.
Dischargeable obligations in the SCIFF framework.
Fundamenta Informaticae, 176(3-4):321--348, 2020.
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DOI ]
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[12]
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Federico Chesani, Giuseppe Cota, Marco Gavanelli, Evelina Lamma, Paola Mello,
and Fabrizio Riguzzi.
Declarative and mathematical programming approaches to decision
support systems for food recycling.
Engineering Applications of Artificial Intelligence, 95:103861,
2020.
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DOI ]
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[11]
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Enzo Losi, Mauro Venturini, Lucrezia Manservigi, Giusppe Fabio Ceschini,
Giovanni. Bechini, Giuseppe Cota, and Fabrizio Riguzzi.
Structured methodology for clustering gas turbine transients by means
of multi-variate time series.
In Proc. ASME Turbo Expo 2020, volume Volume 9: Oil and Gas
Applications; Organic Rankine Cycle Power Systems; Steam Turbine of
Turbo Expo: Power for Land, Sea, and Air, pages 1--16. ASME, 2020.
V009T21A005.
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DOI ]
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[10]
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Giuseppe Cota, Riccardo Zese, Elena Bellodi, Evelina Lamma, and Fabrizio
Riguzzi.
A framework for reasoning on probabilistic description logics.
In Giuseppe Cota, Marilena Daquino, and Gian Luca Pozzato, editors,
Applications and Practices in Ontology Design, Extraction, and
Reasoning, volume 49 of Studies on the Semantic Web, pages 127--144.
IOS Press, © Akademische Verlagsgesellschaft AKA GmbH,
Berlin, 2020.
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[9]
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Fabrizio Riguzzi.
Quantum weighted model counting.
In Giuseppe De Giacomo, Alejandro Catala, Bistra Dilkina, Michela
Milano, Senén Barro, Alberto Bugarín, and Jérôme Lang, editors,
24th European Conference on Artificial Intelligence (ECAI 2020), pages
2640--2647, Amsterdam, Berlin, Washington DC, 2020. © CC BY-NC
4.0, IOS Press.
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DOI |
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.pdf ]
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[8]
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Fabrizio Riguzzi.
Review of Kahl, Patrick Thor; Leclerc, Anthony P.; Tran, Son Cao A
parallel memory-efficient epistemic logic program solver: harder, better,
faster. Ann. Math. Artif. Intell. 86 (2019), no. 1-3, 61–85.
Mathematical Reviews, © American Mathematical
Society, January 2020.
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http ]
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[7]
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Fabrizio Riguzzi.
Review of Costantini, Stefania. About epistemic negation and world
views in epistemic logic programs. Theory Pract. Log. Program. 19 (2019), no.
5-6, 790--807.
Mathematical Reviews, © American Mathematical
Society, May 2020.
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http ]
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[6]
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Fabrizio Riguzzi.
Review of Arieli, Ofer; Borg, AnneMarie; Heyninck, Jesse A review of
the relations between logical argumentation and reasoning with maximal
consistency. Ann. Math. Artif. Intell. 87 (2019), no. 3, 187--226.
Mathematical Reviews, © American Mathematical
Society, 2020.
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http ]
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[5]
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Elena Bellodi, Marco Alberti, Fabrizio Riguzzi, and Riccardo Zese.
MAP inference for probabilistic logic programming.
Theory and Practice of Logic Programming, 20(5):641–655,
© Cambridge University Press, 2020.
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DOI |
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.pdf ]
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[4]
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Damiano Azzolini, Fabrizio Riguzzi, and Evelina Lamma.
An analysis of Gibbs sampling for probabilistic logic programs.
In Carmine Dodaro, George Aristidis Elder, Wolfgang Faber, Jorge
Fandinno, Martin Gebser, Markus Hecher, Emily LeBlanc, Michael Morak, and
Jessica Zangari, editors, Workshop on Probabilistic Logic Programming
(PLP 2020), volume 2678 of CEUR Workshop Proceedings, pages 1--13,
Aachen, Germany, 2020. © by the authors, Sun SITE Central
Europe.
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[3]
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Francesco Ricca, Alessandra Russo, Sergio Greco, Nicola Leone, Alexander
Artikis, Gerhard Friedrich, Paul Fodor, Angelika Kimmig, Francesca A. Lisi,
Marco Maratea, Alessandra Mileo, and Fabrizio Riguzzi, editors.
Proceedings 36th International Conference on Logic Programming
(Technical Communications), number 325 in Electronic Proceedings in
Theoretical Computer Science, 2020.
[ bib |
DOI |
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[2]
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Damiano Azzolini, Elena Bellodi, Alessandro Brancaleoni, Fabrizio Riguzzi, and
Evelina Lamma.
Modeling bitcoin lightning network by logic programming.
In Francesco Ricca, Alessandra Russo, Sergio Greco, Nicola Leone,
Alexander Artikis, Gerhard Friedrich, Paul Fodor, Angelika Kimmig, Francesca
Lisi, Marco Maratea, Alessandra Mileo, and Fabrizio Riguzzi, editors,
Proceedings of the 36th International Conference on Logic Programming
(Technical Communications), pages 258--260, Waterloo, Australia, 2020.
© by the authors, Open Publishing Association.
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[1]
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Damiano Azzolini, Fabrizio Riguzzi, and Evelina Lamma.
Modeling smart contracts with probabilistic logic programming.
In Witold Abramowicz and Gary Klein, editors, Business
Information Systems Workshops, volume 394 of Lecture Notes in Business
Information Processing, pages 86--98, Cham, 2020. © Springer,
Springer International Publishing.
The final publication is available at Springer via
http://dx.doi.org/10.1007/978-3-030-61146-0_7.
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