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A
R. Guidotti, Monreale, A., and Pedreschi, D., “The AI black box Explanation Problem”, ERCIM NEWS, pp. 12–13, 2019.
M. Natilli, Fadda, D., Rinzivillo, S., Pedreschi, D., and Licari, F., “Analysis and Visualization of Performance Indicators in University Admission Tests”, in Formal Methods. FM 2019 International Workshops, Cham, 2020.
L. Pollacci, Guidotti, R., and Rossetti, G., ““Are we playing like Music-Stars?” Placing Emerging Artists on the Italian Music Scene”, 9th International Workshop on Machine Learning and Music, ECML-PKDD. Riva del Garda, 2016.
R. Guidotti and Ruggieri, S., “Assessing the Stability of Interpretable Models”, arXiv preprint arXiv:1810.09352, 2018.
R. Guidotti, Rossetti, G., and Pedreschi, D., “Audio Ergo Sum”, in Federation of International Conferences on Software Technologies: Applications and Foundations, 2016.
B
R. Guidotti, Coscia, M., Pedreschi, D., and Pennacchioli, D., “Behavioral Entropy and Profitability in Retail”, in IEEE International Conference on Data Science and Advanced Analytics (IEEE DSAA'2015), Paris, 2015.
F. Bodria, Giannotti, F., Guidotti, R., Naretto, F., Pedreschi, D., and Rinzivillo, S., “Benchmarking and Survey of Explanation Methods for Black Box Models”, CoRR, vol. abs/2102.13076, 2021.
R. Guidotti, Monreale, A., Matwin, S., and Pedreschi, D., “Black Box Explanation by Learning Image Exemplars in the Latent Feature Space”, in Machine Learning and Knowledge Discovery in Databases, Cham, 2020.
C
R. Guidotti, Monreale, A., Nanni, M., Giannotti, F., and Pedreschi, D., “Clustering Individual Transactional Data for Masses of Users”, in Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2017.
D
S. Bruestle, Pappalardo, L., and Guidotti, R., “Defining Geographic Markets from Probabilistic Clusters: A Machine Learning Algorithm Applied to Supermarket Scanner Data”, Available at SSRN 3452058, 2019.
R. Guidotti, Gabrielli, L., Monreale, A., Pedreschi, D., and Giannotti, F., “Discovering temporal regularities in retail customers’ shopping behavior”, EPJ Data Science, vol. 7, p. 6, 2018.
E
R. Guidotti and Coscia, M., “On the Equivalence Between Community Discovery and Clustering”, in International Conference on Smart Objects and Technologies for Social Good, 2017.
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.
O. Lampridis, Guidotti, R., and Ruggieri, S., “Explaining Sentiment Classification with Synthetic Exemplars and Counter-Exemplars”, in Discovery Science, Cham, 2020.
R. Guidotti, Soldani, J., Neri, D., and Brogi, A., “Explaining successful docker images using pattern mining analysis”, in Federation of International Conferences on Software Technologies: Applications and Foundations, 2018.
M. Natilli, Monreale, A., Guidotti, R., and Pappalardo, L., “Exploring Students Eating Habits Through Individual Profiling and Clustering Analysis”, in ECML PKDD 2018 Workshops, 2018.
F
R. Guidotti, Monreale, A., Giannotti, F., Pedreschi, D., Ruggieri, S., and Turini, F., “Factual and Counterfactual Explanations for Black Box Decision Making”, IEEE Intelligent Systems, 2019.
L. Kotthoff, Nanni, M., Guidotti, R., and O'Sullivan, B., “Find Your Way Back: Mobility Profile Mining with Constraints”, in Principles and Practice of Constraint Programming, Cork, 2015.
L. Pollacci, Guidotti, R., Rossetti, G., Giannotti, F., and Pedreschi, D., “The Fractal Dimension of Music: Geography, Popularity and Sentiment Analysis”, in International Conference on Smart Objects and Technologies for Social Good, 2018.
L. Pollacci, Guidotti, R., Rossetti, G., Giannotti, F., and Pedreschi, D., “The Fractal Dimension of Music: Geography, Popularity and Sentiment Analysis”, in International Conference on Smart Objects and Technologies for Social Good, 2017.
G
M. Nanni, Andrienko, G., Barabasi, A. - L., Boldrini, C., Bonchi, F., Cattuto, C., Chiaromonte, F., Comandé, G., Conti, M., Coté, M., Dignum, F., Dignum, V., Domingo-Ferrer, J., Ferragina, P., Giannotti, F., Guidotti, R., Helbing, D., Kaski, K., Kertész, J., Lehmann, S., Lepri, B., Lukowicz, P., Matwin, S., Jiménez, D. Megías, Monreale, A., Morik, K., Oliver, N., Passarella, A., Passerini, A., Pedreschi, D., Pentland, A., Pianesi, F., Pratesi, F., Rinzivillo, S., Ruggieri, S., Siebes, A., Torra, V., Trasarti, R., van den Hoven, J., and Vespignani, A., “Give more data, awareness and control to individual citizens, and they will help COVID-19 containment”, 2021.
M. Setzu, Guidotti, R., Monreale, A., and Turini, F., “Global Explanations with Local Scoring”, in Machine Learning and Knowledge Discovery in Databases, Cham, 2020.
M. Setzu, Guidotti, R., Monreale, A., Turini, F., Pedreschi, D., and Giannotti, F., “GLocalX - From Local to Global Explanations of Black Box AI Models”, vol. 294, p. 103457, 2021.
R. Guidotti, Coscia, M., Pedreschi, D., and Pennacchioli, D., “Going Beyond GDP to Nowcast Well-Being Using Retail Market Data”, in Advances in Network Science, Springer International Publishing, 2016, pp. 29–42.
H
R. Guidotti, Soldani, J., Neri, D., Brogi, A., and Pedreschi, D., “Helping your docker images to spread based on explainable models”, in Joint European Conference on Machine Learning and Knowledge Discovery in Databases, 2018.

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