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[15]
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Fabrizio Riguzzi.
Quantum weighted model counting.
In Giuseppe De Giacomo, editor, European Conference on
Artificial Intelligence (ECAI 2020), 2020.
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[14]
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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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[13]
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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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[12]
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Fabrizio Riguzzi Michele Fraccaroli, Evelina Lamma.
Automatic setting of dnn hyper-parameters by mixing bayesian
optimization and tuning rules.
In The Sixth International Conference on Machine Learning,
Optimization, and Data Science 2020. To be published., Lecture Notes in
Computer Science. Springer, 2020.
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[11]
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Damiano Azzolini, Fabrizio Riguzzi, and Evelina Lamma.
Analyzing transaction fees with probabilistic logic programming.
In Witold Abramowicz and Rafael Corchuelo, editors, Business
Information Systems Workshops BIS 2019, volume 373 of Lecture Notes in
Business Information Processing, pages 243--254, Cham, 2019. © Springer, Springer International Publishing.
The final publication is available at Springer via
http://dx.doi.org/10.1007/978-3-030-36691-9_21.
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[10]
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Fabrizio Riguzzi.
Quantum weighted model counting.
arXiv, abs/1910.13530, 2019.
[ bib |
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[9]
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Damiano Azzolini, Fabrizio Riguzzi, and Evelina Lamma.
Studying transaction fees in the bitcoin blockchain with
probabilistic logic programming.
Information, 10(11):335, © CCBY, 2019.
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DOI |
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[8]
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Damiano Azzolini, Fabrizio Riguzzi, Evelina Lamma, and Franco Masotti.
A comparison of MCMC sampling for probabilistic logic programming.
In Mario Alviano, Gianluigi Greco, and Francesco Scarcello, editors,
Proceedings of the 18th Conference of the Italian Association for
Artificial Intelligence (AI*IA2019), Rende, Italy 19-22 November 2019,
volume 11946 of Lecture Notes in Computer Science, pages 18--29,
Heidelberg, Germany, 2019. © Springer, Springer.
The final publication is available at Springer via
http://dx.doi.org/10.1007/978-3-030-35166-3_2.
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[7]
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Fabrizio Riguzzi, Kristian Kersting, Marco Lippi, and Sriraam Natarajan.
Editorial: Statistical relational artificial intelligence.
Frontiers in Robotics and AI, 6:68, © by the
authors, 2019.
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DOI |
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[6]
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Giuseppe Cota, Fabrizio Riguzzi, Evelina Lamma, and Riccardo Zese.
KRaider: a crawler for linked data.
In Alberto Casagrande and Eugenio Omodeo, editors, Proceedings
of the 34th Italian Conference on Computational Logic, volume 2396 of
CEUR Workshop Proceedings, pages 202--216, Aachen, Germany, 2019.
© by the authors, Sun SITE Central Europe.
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[5]
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Arnaud Nguembang Fadja and Fabrizio Riguzzi.
Lifted discriminative learning of probabilistic logic programs.
Machine Learning, 108(7):1111--1135, © Springer,
2019.
The original publication is available at
http://link.springer.com.
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[4]
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Nicolas Lachiche, Christel Vrain, Fabrizio Riguzzi, Bellodi Elena, and Zese
Riccardo.
Preface to special issue on Inductive Logic Programming, ILP 2017
and 2018.
Machine Learning, pages 1--3, 2019.
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[3]
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Riccardo Zese, Giuseppe Cota, Evelina Lamma, Elena Bellodi, and Fabrizio
Riguzzi.
Probabilistic DL reasoning with pinpointing formulas: A
prolog-based approach.
Theory and Practice of Logic Programming, 19(3):449--476,
© Cambridge University Press, 2019.
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DOI |
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[2]
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Fabrizio Riguzzi.
Review of Avanzini, Martin; Dal Lago, Ugo. On sharing, memoization,
and polynomial time. Inform. and Comput. 261 (2018), part 1, 3--22.
Mathematical Reviews, © American Mathematical
Society, January 2019.
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[1]
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Jan Wielemaker, Fabrizio Riguzzi, Bob Kowalski, Torbjörn Lager, Fariba Sadri,
and Miguel Calejo.
Using SWISH to realise interactive web based tutorials for logic
based languages.
Theory and Practice of Logic Programming, 19(2):229--261,
© Cambridge University Press, 2019.
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