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M. de Leoni, Lanciano, G., and Marrella, A., “A Tool for Aligning Event Logs and Prescriptive Process Models through Automated Planning”, in Proceedings of the BPM Demo Track and BPM Dissertation Award co-located with 15th International Conference on Business Process Modeling (BPM 2017), 2017.
D. Brunato, De Mattei, L., Dell’Orletta, F., Iavarone, B., and Venturi, G., “Is this Sentence Difficult? Do you Agree?”, in Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, 2018.
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V. Macchiati, Brandi, G., Di Matteo, T., Paolotti, D., Caldarelli, G., and Cimini, G., “Systemic liquidity contagion in the European interbank market”, Journal of Economic Interaction and Coordination, 2021.
I. A. Ortiz-Rodríguez, Raventós, J., Mújica, E., González-Hernández, E., Vega-Peña, E., Ortega-Larrocea, P., Bonet, A., and Merow, C., “Spatiotemporal effects of Hurricane Ivan on an endemic epiphytic orchid: 10 years of follow-up”, Plant Ecology & Diversity , vol. 13, 2020, no. 1, 2020.
G. Lanciano, Ritacco, A., Cucinotta, T., Vannucci, M., Artale, A., Basili, L., Sposato, E., and Barata, J., “SOM-Based Behavioral Analysis for Virtualized Network Functions”, in Proceedings of the 35th Annual ACM Symposium on Applied Computing, New York, NY, USA, 2020.
F. Galli, Ritacco, A., Lanciano, G., Vannocci, M., Colla, V., and Vannucci, M., “Self-supervised pre-training of CNNs for flatness defect classification in the steelworks industry”, International Journal of Advances in Intelligent Informatics, vol. 6, pp. 13–22, 2020.
A. Bonavita, Guidotti, R., and Nanni, M., “Self-Adapting Trajectory Segmentation”, in 3rd International Workshop on Big Mobility Data Analytics (BMDA) 2020, 2020.
A. Bonavita, “Search for H-> mu mu in the VBF production channel with the CMS experiment at LHC”, 2018.
Q
M. Andreani, Candila, V., and Petrella, L., “Quantile Regression Forest with mixed-frequency data”, vol. Book of Short Papers SIS 2021. Pearson, 2021.
M. Andreani, Candila, V., and Petrella, L., “Quantile Regression Forest for Value-at-Risk Forecasting Via Mixed-Frequency Data”, Mathematical and Statistical Methods for Actuarial Sciences and Finance. Springer, Cham, 2022.
G. Gorrell, Roberts, I., Greenwood, M. A., Bakir, M. E., Iavarone, B., and Bontcheva, K., “Quantifying media influence and partisan attention on Twitter during the UK EU referendum”, in International Conference on Social Informatics, 2018.
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G. Gorrell, Bakir, M. E., Roberts, I., Greenwood, M. A., Iavarone, B., and Bontcheva, K., “Partisanship, propaganda and post-truth politics: Quantifying impact in online”, arXiv preprint arXiv:1902.01752, 2019.
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D. Di Gangi, Sardo, D. R. Lo, Macchiati, V., Minh, T. P., Pinotti, F., Ramadiah, A., Wilinski, M., Barucca, P., and Cimini, G., “Network Sensitivity of Systemic Risk”, Journal of Network Theory in Finance, 2019.
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M. Andreani, Candila, V., Morelli, G., and Petrella, L., “Multivariate Analysis of Energy Commodities during the COVID-19 Pandemic: Evidence from a Mixed-Frequency Approach”, Risks, vol. 9, p. 144, 2021.
G. Lanciano and de Leoni, M., “Models and Logs used in the paper ‘Aligning Partially-Ordered Process-Execution Traces and Models Using Automated Planning’ accepted for ICAPS 2018”. TU Eindhoven, 2018.
V. Voukelatou, Gabrielli, L., Miliou, I., Cresci, S., Sharma, R., Tesconi, M., and Pappalardo, L., “Measuring objective and subjective well-being: dimensions and data sources”, International Journal of Data Science and Analytics (JDSA), 2020.
M. Baltakiene, Baltakys, K., Cardamone, D., Parisi, F., Radicioni, T., Torricelli, M., de Jeude, J. A., and Saracco, F., “Maximum entropy approach to link prediction in bipartite networks”, arXiv preprint arXiv:1805.04307, 2018.
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S. Corbara, Moreo, A., Sebastiani, F., and Tavoni, M., “L’Epistola a Cangrande al vaglio della Computational Authorship Verification: risultati preliminari (con una postilla sulla cosiddetta “XIV Epistola di Dante Alighieri”)”, in Nuove inchieste sull’epistola a Cangrande: atti della giornata di studi, Pisa 18 dicembre 2018, 2020.
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G. Tripodi, Chiaromonte, F., and Lillo, F., “Knowledge and Social Relatedness Shape Research Portfolio Diversification”, Scientific Reports, vol. 10, no. 1, 2020.
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A. Sirbu, Andrienko, G., Andrienko, N., Boldrini, C., Conti, M., Giannotti, F., Guidotti, R., Bertoli, S., Kim, J., Muntean, C. Ioana, and others, “Human migration: the big data perspective”, International Journal of Data Science and Analytics, pp. 1–20, 2020.
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C. Panigutti, Guidotti, R., Monreale, A., and Pedreschi, D., “Explaining multi-label black-box classifiers for health applications”, in International Workshop on Health Intelligence, 2019.
S. Corbara, Moreo, A., Sebastiani, F., and Tavoni, M., “The Epistle to Cangrande Through the Lens of Computational Authorship Verification”, in New Trends in Image Analysis and Processing – ICIAP 2019, Cham, 2019.
C. Carugno and Radicioni, T., “ECHO CHAMBERS E POLARIZZAZIONE Uno sguardo critico sulla diffusione dell’informazione nei social network”, The Lab’s Quarterly, vol. 20, no. 4, 2018.
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M. Andreani and Petrella, L., “Dynamic Quantile Regression Forest”, SIS 2020 - 50th Conference of the Italian Statistical Society, vol. Book of Short Papers SIS 2020. Pearson, 2020.
V. Dib, Nalon, M. Aurélio, Amazonas, N. Tavares, Vidal, C. Yuri, Ortiz-Rodríguez, I. A., Daněk, J., de Oliveira, M. Formis, Alberti, P., da Silva, R. Aparecida, Precinoto, R. Salomão, and Gomes, T. Figueiredo, “Drivers of change in biodiversity and ecosystem services in the Cantareira System Protected Area : A prospective analysis of the implementation of public policies”, Biota Neotropica, vol. 20, no. 1, 2020.
F. Lamperti, Malerba, F., Mavilia, R., and Tripodi, G., “Does the position in the inter-sectoral knowledge space affect the international competitiveness of industries?”, Economics of Innovation and New Technology, pp. 1–48, 2019.
C. Panigutti, Perotti, A., and Pedreschi, D., “Doctor XAI: an ontology-based approach to black-box sequential data classification explanations”, in Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency, 2020.
J. Kim, Sirbu, A., Giannotti, F., and Gabrielli, L., “Digital Footprints of International Migration on Twitter”, in International Symposium on Intelligent Data Analysis, 2020.
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N. Atanov, Baranov, V., Budagov, J., Cervelli, F., Colao, F., Cordelli, M., Corradi, G., Dané, E., Davydov, Y. I., Di Falco, S., Diociaiuti, E., Donati, S., Donghia, R., Echenard, B., Flood, K., Giovannella, S., Glagolev, V., Grancagnolo, F., Happacher, F., Hitlin, D. G., Martini, M., Miscetti, S., Miyashita, T., Morescalchi, L., Murat, P., Pezzullo, G., Porter, F., Raffaelli, F., Radicioni, T., Ricci, M., Saputi, A., Sarra, I., Spinella, F., Tassielli, G., Tereshchenko, V., Usubov, Z., and Zhu, R. Y., “The calorimeter of the Mu2e experiment at Fermilab”, Journal of Instrumentation, vol. 12, 2017.
T. Radicioni, “Calibration and performance optimization of the Electromagnetic Calorimeter in Mu2e”, 2016.
A
C. Panigutti, Tizzoni, M., Bajardi, P., Smoreda, Z., and Colizza, V., “Assessing the use of mobile phone data to describe recurrent mobility patterns in spatial epidemic models”, Royal Society open science, vol. 4, p. 160950, 2017.
M. de Leoni, Lanciano, G., and Marrella, A., “Aligning Partially-Ordered Process-Execution Traces and Models Using Automated Planning”, in 28th International Conference on Automated Planning and Scheduling (ICAPS 2018), 2018.
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