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2020 – today
- 2024
[j36]Francesco Spinnato
, Riccardo Guidotti, Anna Monreale, Mirco Nanni:
Fast, Interpretable, and Deterministic Time Series Classification With a Bag-of-Receptive-Fields. IEEE Access 12: 137893-137912 (2024)- [j35]Simone Piaggesi, Francesco Bodria, Riccardo Guidotti, Fosca Giannotti, Dino Pedreschi:
Counterfactual and Prototypical Explanations for Tabular Data via Interpretable Latent Space. IEEE Access 12: 168983-169000 (2024) - [j34]Riccardo Guidotti:
Counterfactual explanations and how to find them: literature review and benchmarking. Data Min. Knowl. Discov. 38(5): 2770-2824 (2024) - [j33]Riccardo Guidotti, Anna Monreale, Salvatore Ruggieri, Francesca Naretto, Franco Turini, Dino Pedreschi, Fosca Giannotti:
Stable and actionable explanations of black-box models through factual and counterfactual rules. Data Min. Knowl. Discov. 38(5): 2825-2862 (2024) - [j32]Andrea Cossu, Francesco Spinnato, Riccardo Guidotti, Davide Bacciu:
Drifting explanations in continual learning. Neurocomputing 597: 127960 (2024) - [j31]Luca Longo, Mario Brcic, Federico Cabitza, Jaesik Choi, Roberto Confalonieri, Javier Del Ser, Riccardo Guidotti, Yoichi Hayashi, Francisco Herrera, Andreas Holzinger, Richard Jiang, Hassan Khosravi, Freddy Lécué, Gianclaudio Malgieri, Andrés Páez, Wojciech Samek, Johannes Schneider, Timo Speith, Simone Stumpf:
Explainable Artificial Intelligence (XAI) 2.0: A manifesto of open challenges and interdisciplinary research directions. Inf. Fusion 106: 102301 (2024) - [j30]Salvatore Lusito, Andrea Pugnana, Riccardo Guidotti:
Solving imbalanced learning with outlier detection and features reduction. Mach. Learn. 113(8): 5273-5330 (2024) - [j29]Andrea Fedele, Riccardo Guidotti, Dino Pedreschi:
Explaining Siamese networks in few-shot learning. Mach. Learn. 113(10): 7723-7760 (2024) - [j28]Alessandro Berti, Anna Bernasconi, Gianna M. Del Corso, Riccardo Guidotti:
The role of encodings and distance metrics for the quantum nearest neighbor. Quantum Mach. Intell. 6(2): 62 (2024) - [j27]Anna Bernasconi, Alessandro Berti, Gianna M. Del Corso, Riccardo Guidotti, Alessandro Poggiali:
Quantum subroutine for variance estimation: algorithmic design and applications. Quantum Mach. Intell. 6(2): 78 (2024) - [j26]Alessandro Poggiali, Alessandro Berti, Anna Bernasconi, Gianna M. Del Corso, Riccardo Guidotti:
Quantum clustering with k-Means: A hybrid approach. Theor. Comput. Sci. 992: 114466 (2024) - [j25]Francesco Spinnato, Riccardo Guidotti, Anna Monreale, Mirco Nanni, Dino Pedreschi, Fosca Giannotti:
Understanding Any Time Series Classifier with a Subsequence-based Explainer. ACM Trans. Knowl. Discov. Data 18(2): 36:1-36:34 (2024) - [c79]Riccardo Guidotti, Anna Monreale, Mattia Setzu, Giulia Volpi:
Generative Model for Decision Trees. AAAI 2024: 21116-21124 - [c78]Andrea Beretta, Gianmario Ercoli, Alfonso Ferraro, Riccardo Guidotti, Andrea Iommi, Antonio Mastropietro, Anna Monreale, Daniela Rotelli, Salvatore Ruggieri:
Requirements of eXplainable AI in Algorithmic Hiring. AIMMES 2024 - [c77]Cristiano Landi, Riccardo Guidotti:
A Shape-Based Map Matching Approach for Geographic Transferability of Discriminative Subtrajectories. EDBT/ICDT Workshops 2024 - [c76]Marta Marchiori Manerba, Karolina Stanczak, Riccardo Guidotti, Isabelle Augenstein:
Social Bias Probing: Fairness Benchmarking for Language Models. EMNLP 2024: 14653-14671 - [c75]Guillermo Fernández, Riccardo Guidotti, Fosca Giannotti, Mattia Setzu, Juan A. Aledo, José A. Gámez, José Miguel Puerta:
FLocalX - Local to Global Fuzzy Explanations for Black Box Classifiers. IDA (2) 2024: 197-209 - [c74]Federico Mazzoni, Riccardo Guidotti, Alessio Malizia:
A Frank System for Co-Evolutionary Hybrid Decision-Making. IDA (2) 2024: 236-248 - [c73]Alessio Cascione, Mattia Setzu, Riccardo Guidotti:
Data-Agnostic Pivotal Instances Selection for Decision-Making Models. ECML/PKDD (1) 2024: 367-386 - [c72]Martina Cinquini, Riccardo Guidotti:
Causality-Aware Local Interpretable Model-Agnostic Explanations. xAI (3) 2024: 108-124 - [i22]Federico Mazzoni, Roberto Pellungrini, Riccardo Guidotti:
Bridging the Gap in Hybrid Decision-Making Systems. CoRR abs/2409.19415 (2024) - 2023
- [j24]Francesco Bodria, Fosca Giannotti, Riccardo Guidotti, Francesca Naretto, Dino Pedreschi, Salvatore Rinzivillo:
Benchmarking and survey of explanation methods for black box models. Data Min. Knowl. Discov. 37(5): 1719-1778 (2023) - [j23]Sajid Ali, Tamer Abuhmed, Shaker H. Ali El-Sappagh, Khan Muhammad, Jose Maria Alonso-Moral, Roberto Confalonieri, Riccardo Guidotti, Javier Del Ser, Natalia Díaz Rodríguez, Francisco Herrera:
Explainable Artificial Intelligence (XAI): What we know and what is left to attain Trustworthy Artificial Intelligence. Inf. Fusion 99: 101805 (2023) - [j22]Orestis Lampridis, Laura State, Riccardo Guidotti, Salvatore Ruggieri:
Explaining short text classification with diverse synthetic exemplars and counter-exemplars. Mach. Learn. 112(11): 4289-4322 (2023) - [c71]Giuseppe Cianci, Roberto Goglia, Riccardo Guidotti, Matteo Kapllaj, Roberto Mosca, Andrea Pugnana, Franco Ricotti, Salvatore Ruggieri:
Applied Data Science for Leasing Score Prediction. IEEE Big Data 2023: 1687-1696 - [c70]Mattia Poggioli, Francesco Spinnato, Riccardo Guidotti:
Text to Time Series Representations: Towards Interpretable Predictive Models. DS 2023: 230-245 - [c69]Federico Mazzoni, Marta Marchiori Manerba, Martina Cinquini, Riccardo Guidotti, Salvatore Ruggieri:
GenFair: A Genetic Fairness-Enhancing Data Generation Framework. DS 2023: 356-371 - [c68]Riccardo Guidotti, Cristiano Landi, Andrea Beretta, Daniele Fadda, Mirco Nanni:
Interpretable Data Partitioning Through Tree-Based Clustering Methods. DS 2023: 492-507 - [c67]Andrea Cossu, Francesco Spinnato, Riccardo Guidotti, Davide Bacciu:
A Protocol for Continual Explanation of SHAP. ESANN 2023 - [c66]Alessandro Poggiali, Anna Bernasconi, Alessandro Berti, Gianna M. Del Corso, Riccardo Guidotti:
Quantum Feature Selection with Variance Estimation. ESANN 2023 - [c65]Cristiano Landi, Riccardo Guidotti, Mirco Nanni, Anna Monreale:
The Trajectory Interval Forest Classifier for Trajectory Classification. SIGSPATIAL/GIS 2023: 67:1-67:4 - [c64]Cristiano Landi, Francesco Spinnato, Riccardo Guidotti, Anna Monreale, Mirco Nanni:
Geolet: An Interpretable Model for Trajectory Classification. IDA 2023: 236-248 - [c63]Fosca Giannotti, Riccardo Guidotti, Anna Monreale, Luca Pappalardo, Dino Pedreschi, Roberto Pellungrini, Francesca Pratesi, Salvatore Rinzivillo, Salvatore Ruggieri, Mattia Setzu, Rosaria Deluca:
Trustworthy AI at KDD Lab. Ital-IA 2023: 388-393 - [c62]Luca Corbucci, Riccardo Guidotti, Anna Monreale:
Explaining Black-Boxes in Federated Learning. xAI (2) 2023: 151-163 - [c61]Martina Cinquini, Fosca Giannotti, Riccardo Guidotti, Andrea Mattei:
Handling Missing Values in Local Post-hoc Explainability. xAI (2) 2023: 256-278 - [e11]Cataldo Musto, Riccardo Guidotti, Anna Monreale, Erasmo Purificato, Giovanni Semeraro:
Proceedings of the 4th Italian Workshop on Explainable Artificial Intelligence co-located with 22nd International Conference of the Italian Association for Artificial Intelligence(AIxIA 2023), Roma, Italy, November 8, 2023. CEUR Workshop Proceedings 3518, CEUR-WS.org 2023 [contents] - [e10]Irena Koprinska, Paolo Mignone, Riccardo Guidotti, Szymon Jaroszewicz, Holger Fröning, Francesco Gullo, Pedro M. Ferreira, Damian Roqueiro, Gaia Ceddia, Slawomir Nowaczyk, João Gama, Rita P. Ribeiro, Ricard Gavaldà, Elio Masciari, Zbigniew W. Ras, Ettore Ritacco, Francesca Naretto, Andreas Theissler, Przemyslaw Biecek, Wouter Verbeke, Gregor Schiele, Franz Pernkopf, Michaela Blott, Ilaria Bordino, Ivan Luciano Danesi, Giovanni Ponti, Lorenzo Severini, Annalisa Appice, Giuseppina Andresini, Ibéria Medeiros, Guilherme Graça, Lee Cooper, Naghmeh Ghazaleh, Jonas Richiardi, Diego Saldana Miranda, Konstantinos Sechidis, Arif Canakoglu, Sara Pidò, Pietro Pinoli, Albert Bifet, Sepideh Pashami:
Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2022, Grenoble, France, September 19-23, 2022, Proceedings, Part I. Communications in Computer and Information Science 1752, Springer 2023, ISBN 978-3-031-23617-4 [contents] - [e9]Irena Koprinska, Paolo Mignone, Riccardo Guidotti, Szymon Jaroszewicz, Holger Fröning, Francesco Gullo, Pedro M. Ferreira, Damian Roqueiro, Gaia Ceddia, Slawomir Nowaczyk, João Gama, Rita P. Ribeiro, Ricard Gavaldà, Elio Masciari, Zbigniew W. Ras, Ettore Ritacco, Francesca Naretto, Andreas Theissler, Przemyslaw Biecek, Wouter Verbeke, Gregor Schiele, Franz Pernkopf, Michaela Blott, Ilaria Bordino, Ivan Luciano Danesi, Giovanni Ponti, Lorenzo Severini, Annalisa Appice, Giuseppina Andresini, Ibéria Medeiros, Guilherme Graça, Lee Cooper, Naghmeh Ghazaleh, Jonas Richiardi, Diego Saldana Miranda, Konstantinos Sechidis, Arif Canakoglu, Sara Pidò, Pietro Pinoli, Albert Bifet, Sepideh Pashami:
Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2022, Grenoble, France, September 19-23, 2022, Proceedings, Part II. Communications in Computer and Information Science 1753, Springer 2023, ISBN 978-3-031-23632-7 [contents] - [i21]Martina Cinquini, Fosca Giannotti, Riccardo Guidotti:
Boosting Synthetic Data Generation with Effective Nonlinear Causal Discovery. CoRR abs/2301.07427 (2023) - [i20]Carlo Metta, Riccardo Guidotti, Yuan Yin, Patrick Gallinari, Salvatore Rinzivillo:
Exemplars and Counterexemplars Explanations for Image Classifiers, Targeting Skin Lesion Labeling. CoRR abs/2302.03033 (2023) - [i19]Andrea Cossu, Francesco Spinnato, Riccardo Guidotti, Davide Bacciu:
A Protocol for Continual Explanation of SHAP. CoRR abs/2306.07218 (2023) - [i18]Riccardo Guidotti, Salvatore Ruggieri:
Ensemble of Counterfactual Explainers. CoRR abs/2308.15194 (2023) - [i17]Luca Longo, Mario Brcic, Federico Cabitza, Jaesik Choi, Roberto Confalonieri, Javier Del Ser, Riccardo Guidotti, Yoichi Hayashi, Francisco Herrera, Andreas Holzinger, Richard Jiang, Hassan Khosravi, Freddy Lécué, Gianclaudio Malgieri, Andrés Páez, Wojciech Samek, Johannes Schneider, Timo Speith, Simone Stumpf:
Explainable Artificial Intelligence (XAI) 2.0: A Manifesto of Open Challenges and Interdisciplinary Research Directions. CoRR abs/2310.19775 (2023) - [i16]Marta Marchiori Manerba, Karolina Stanczak, Riccardo Guidotti, Isabelle Augenstein:
Social Bias Probing: Fairness Benchmarking for Language Models. CoRR abs/2311.09090 (2023) - [i15]Francesco Spinnato, Riccardo Guidotti, Anna Monreale, Mirco Nanni:
A Bag of Receptive Fields for Time Series Extrinsic Predictions. CoRR abs/2311.18029 (2023) - [i14]Francesco Spinnato, Riccardo Guidotti, Anna Monreale:
An Explanation that LASTS: Understanding Any Time Series Classifier. ERCIM News 2023(134) (2023) - 2022
- [j21]Andreas Theissler, Francesco Spinnato, Udo Schlegel, Riccardo Guidotti:
Explainable AI for Time Series Classification: A Review, Taxonomy and Research Directions. IEEE Access 10: 100700-100724 (2022) - [j20]Agnese Bonavita, Riccardo Guidotti, Mirco Nanni:
Individual and collective stop-based adaptive trajectory segmentation. GeoInformatica 26(3): 451-477 (2022) - [j19]Mirco Nanni, Riccardo Guidotti, Agnese Bonavita, Omid Isfahani Alamdari:
City indicators for geographical transfer learning: an application to crash prediction. GeoInformatica 26(4): 581-612 (2022) - [j18]Riccardo Guidotti:
Exploiting auto-encoders for explaining black-box classifiers. Intelligenza Artificiale 16(1): 115-129 (2022) - [c60]Mahtab Sarvmaili, Riccardo Guidotti, Anna Monreale, Amílcar Soares, Zahra Sadeghi, Fosca Giannotti, Dino Pedreschi, Stan Matwin:
A Modularized Framework for Explaining Black Box Classifiers for Text Data. Canadian AI 2022 - [c59]Marta Marchiori Manerba, Riccardo Guidotti:
Investigating Debiasing Effects on Classification and Explainability. AIES 2022: 468-478 - [c58]Andrea Fedele, Riccardo Guidotti, Dino Pedreschi:
Explaining Siamese Networks in Few-Shot Learning for Audio Data. DS 2022: 509-524 - [c57]Francesco Bodria, Riccardo Guidotti, Fosca Giannotti, Dino Pedreschi:
Interpretable Latent Space to Enable Counterfactual Explanations. DS 2022: 525-540 - [c56]Francesco Spinnato, Riccardo Guidotti, Mirco Nanni, Daniele Maccagnola, Giulia Paciello, Antonio Bencini Farina:
Explaining Crash Predictions on Multivariate Time Series Data. DS 2022: 556-566 - [c55]Francesco Bodria, Riccardo Guidotti, Fosca Giannotti, Dino Pedreschi:
Transparent Latent Space Counterfactual Explanations for Tabular Data. DSAA 2022: 1-10 - [c54]Daniela Rotelli, Anna Monreale, Riccardo Guidotti:
Uncovering Student Temporal Learning Patterns. EC-TEL 2022: 340-353 - [c53]Carlo Metta, Riccardo Guidotti, Yuan Yin, Patrick Gallinari, Salvatore Rinzivillo:
Exemplars and Counterexemplars Explanations for Skin Lesion Classifiers. HHAI 2022: 258-260 - [c52]Alessandro Poggiali, Alessandro Berti, Anna Bernasconi, Gianna Maria Del Corso, Riccardo Guidotti:
Clustering Classical Data with Quantum k-Means. ICTCS 2022: 188-200 - [c51]Marta Marchiori Manerba, Riccardo Guidotti, Lucia C. Passaro, Salvatore Ruggieri:
Bias Discovery within Human Raters: A Case Study of the Jigsaw Dataset. NLPerspectives@LREC 2022: 26-31 - [c50]Alessandro Berti, Anna Bernasconi, Gianna M. Del Corso, Riccardo Guidotti:
Effect of Different Encodings and Distance Functions on Quantum Instance-Based Classifiers. PAKDD (2) 2022: 96-108 - [c49]Francesco Bodria, Salvatore Rinzivillo, Daniele Fadda, Riccardo Guidotti, Fosca Giannotti, Dino Pedreschi:
Explaining Black Box with Visual Exploration of Latent Space. EuroVis (Short Papers) 2022: 85-89 - [e8]Cataldo Musto, Riccardo Guidotti, Anna Monreale, Giovanni Semeraro:
Proceedings of the 3rd Italian Workshop on Explainable Artificial Intelligence co-located with 21th International Conference of the Italian Association for Artificial Intelligence(AIxIA 2022), Udine, Italy, November 28 - December 3, 2022. CEUR Workshop Proceedings 3277, CEUR-WS.org 2022 [contents] - [i13]Martina Cinquini, Riccardo Guidotti:
CALIME: Causality-Aware Local Interpretable Model-Agnostic Explanations. CoRR abs/2212.05256 (2022) - [i12]Alessandro Poggiali, Alessandro Berti, Anna Bernasconi, Gianna M. Del Corso, Riccardo Guidotti:
Quantum Clustering with k-Means: a Hybrid Approach. CoRR abs/2212.06691 (2022) - 2021
- [j17]Riccardo Guidotti:
Evaluating local explanation methods on ground truth. Artif. Intell. 291: 103428 (2021) - [j16]Mattia Setzu, Riccardo Guidotti, Anna Monreale, Franco Turini, Dino Pedreschi, Fosca Giannotti:
GLocalX - From Local to Global Explanations of Black Box AI Models. Artif. Intell. 294: 103457 (2021) - [j15]Mirco Nanni, Gennady L. Andrienko, Albert-László Barabási, Chiara Boldrini, Francesco Bonchi, Ciro Cattuto, Francesca Chiaromonte, Giovanni Comandè, Marco Conti, Mark Coté, Frank Dignum, Virginia Dignum, Josep Domingo-Ferrer, Paolo Ferragina, Fosca Giannotti, Riccardo Guidotti, Dirk Helbing, Kimmo Kaski, János Kertész, Sune Lehmann, Bruno Lepri, Paul Lukowicz, Stan Matwin, David Megías Jiménez, Anna Monreale, Katharina Morik, Nuria Oliver, Andrea Passarella, Andrea Passerini, Dino Pedreschi, Alex Pentland, Fabio Pianesi, Francesca Pratesi, Salvatore Rinzivillo, Salvatore Ruggieri, Arno Siebes, Vicenç Torra, Roberto Trasarti, Jeroen van den Hoven, Alessandro Vespignani:
Give more data, awareness and control to individual citizens, and they will help COVID-19 containment. Ethics Inf. Technol. 23(S1): 1-6 (2021) - [j14]Riccardo Guidotti, Matteo D'Onofrio:
Matrix Profile-Based Interpretable Time Series Classifier. Frontiers Artif. Intell. 4: 699448 (2021) - [j13]Gennady L. Andrienko, Natalia V. Andrienko, Chiara Boldrini, Guido Caldarelli, Paolo Cintia, Stefano Cresci, Angelo Facchini, Fosca Giannotti, Aristides Gionis, Riccardo Guidotti, Michael Mathioudakis, Cristina Ioana Muntean, Luca Pappalardo, Dino Pedreschi, Evangelos Pournaras, Francesca Pratesi, Maurizio Tesconi, Roberto Trasarti:
(So) Big Data and the transformation of the city. Int. J. Data Sci. Anal. 11(4): 311-340 (2021) - [j12]Alina Sîrbu, Gennady L. Andrienko, Natalia V. Andrienko, Chiara Boldrini, Marco Conti, Fosca Giannotti, Riccardo Guidotti, Simone Bertoli, Jisu Kim, Cristina Ioana Muntean, Luca Pappalardo, Andrea Passarella, Dino Pedreschi, Laura Pollacci, Francesca Pratesi, Rajesh Sharma:
Human migration: the big data perspective. Int. J. Data Sci. Anal. 11(4): 341-360 (2021) - [j11]Alina Sîrbu, Gennady L. Andrienko, Natalia V. Andrienko, Chiara Boldrini, Marco Conti, Fosca Giannotti, Riccardo Guidotti, Simone Bertoli, Jisu Kim, Cristina Ioana Muntean, Luca Pappalardo, Andrea Passarella, Dino Pedreschi, Laura Pollacci, Francesca Pratesi, Rajesh Sharma:
Correction to: Human migration: the big data perspective. Int. J. Data Sci. Anal. 12(1): 77 (2021) - [c48]Mahtab Sarvmaili, Amílcar Soares, Riccardo Guidotti, Anna Monreale, Fosca Giannotti, Dino Pedreschi, Stan Matwin:
A modularized framework for explaining hierarchical attention networks on text classifiers. Canadian AI 2021 - [c47]Riccardo Guidotti, Anna Monreale:
Designing Shapelets for Interpretable Data-Agnostic Classification. AIES 2021: 532-542 - [c46]Marta Marchiori Manerba, Riccardo Guidotti:
FairShades: Fairness Auditing via Explainability in Abusive Language Detection Systems. CogMI 2021: 34-43 - [c45]Martina Cinquini, Fosca Giannotti, Riccardo Guidotti:
Boosting Synthetic Data Generation with Effective Nonlinear Causal Discovery. CogMI 2021: 54-63 - [c44]Valerio Bonsignori, Riccardo Guidotti, Anna Monreale:
Deriving a Single Interpretable Model by Merging Tree-Based Classifiers. DS 2021: 347-357 - [c43]Riccardo Guidotti, Salvatore Ruggieri:
Ensemble of Counterfactual Explainers. DS 2021: 358-368 - [c42]Mirco Nanni, Agnese Bonavita, Riccardo Guidotti:
City Indicators for Mobility Data Mining. EDBT/ICDT Workshops 2021 - [c41]Carlo Metta, Riccardo Guidotti, Yuan Yin, Patrick Gallinari, Salvatore Rinzivillo:
Exemplars and Counterexemplars Explanations for Image Classifiers, Targeting Skin Lesion Labeling. ISCC 2021: 1-7 - [e7]Michael Kamp, Irena Koprinska, Adrien Bibal, Tassadit Bouadi, Benoît Frénay, Luis Galárraga, José Oramas, Linara Adilova, Yamuna Krishnamurthy, Bo Kang, Christine Largeron, Jefrey Lijffijt, Tiphaine Viard, Pascal Welke, Massimiliano Ruocco, Erlend Aune, Claudio Gallicchio, Gregor Schiele, Franz Pernkopf, Michaela Blott, Holger Fröning, Günther Schindler, Riccardo Guidotti, Anna Monreale, Salvatore Rinzivillo, Przemyslaw Biecek, Eirini Ntoutsi, Mykola Pechenizkiy, Bodo Rosenhahn, Christopher L. Buckley, Daniela Cialfi, Pablo Lanillos, Maxwell Ramstead, Tim Verbelen, Pedro M. Ferreira, Giuseppina Andresini, Donato Malerba, Ibéria Medeiros, Philippe Fournier-Viger, M. Saqib Nawaz, Sebastián Ventura, Meng Sun, Min Zhou, Valerio Bitetta, Ilaria Bordino, Andrea Ferretti, Francesco Gullo, Giovanni Ponti, Lorenzo Severini, Rita P. Ribeiro, João Gama, Ricard Gavaldà, Lee Cooper, Naghmeh Ghazaleh, Jonas Richiardi, Damian Roqueiro, Diego Saldana Miranda, Konstantinos Sechidis, Guilherme Graça:
Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2021, Virtual Event, September 13-17, 2021, Proceedings, Part I. Communications in Computer and Information Science 1524, Springer 2021, ISBN 978-3-030-93735-5 [contents] - [e6]Michael Kamp, Irena Koprinska, Adrien Bibal, Tassadit Bouadi, Benoît Frénay, Luis Galárraga, José Oramas, Linara Adilova, Yamuna Krishnamurthy, Bo Kang, Christine Largeron, Jefrey Lijffijt, Tiphaine Viard, Pascal Welke, Massimiliano Ruocco, Erlend Aune, Claudio Gallicchio, Gregor Schiele, Franz Pernkopf, Michaela Blott, Holger Fröning, Günther Schindler, Riccardo Guidotti, Anna Monreale, Salvatore Rinzivillo, Przemyslaw Biecek, Eirini Ntoutsi, Mykola Pechenizkiy, Bodo Rosenhahn, Christopher L. Buckley, Daniela Cialfi, Pablo Lanillos, Maxwell Ramstead, Tim Verbelen, Pedro M. Ferreira, Giuseppina Andresini, Donato Malerba, Ibéria Medeiros, Philippe Fournier-Viger, M. Saqib Nawaz, Sebastián Ventura, Meng Sun, Min Zhou, Valerio Bitetta, Ilaria Bordino, Andrea Ferretti, Francesco Gullo, Giovanni Ponti, Lorenzo Severini, Rita P. Ribeiro, João Gama, Ricard Gavaldà, Lee Cooper, Naghmeh Ghazaleh, Jonas Richiardi, Damian Roqueiro, Diego Saldana Miranda, Konstantinos Sechidis, Guilherme Graça:
Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2021, Virtual Event, September 13-17, 2021, Proceedings, Part II. Communications in Computer and Information Science 1525, Springer 2021, ISBN 978-3-030-93732-4 [contents] - [i11]Mattia Setzu, Riccardo Guidotti, Anna Monreale, Franco Turini, Dino Pedreschi, Fosca Giannotti:
GLocalX - From Local to Global Explanations of Black Box AI Models. CoRR abs/2101.07685 (2021) - [i10]Francesco Bodria, Fosca Giannotti, Riccardo Guidotti, Francesca Naretto, Dino Pedreschi, Salvatore Rinzivillo:
Benchmarking and Survey of Explanation Methods for Black Box Models. CoRR abs/2102.13076 (2021) - [i9]Carlo Metta, Andrea Beretta, Riccardo Guidotti, Yuan Yin, Patrick Gallinari, Salvatore Rinzivillo, Fosca Giannotti:
Explainable Deep Image Classifiers for Skin Lesion Diagnosis. CoRR abs/2111.11863 (2021) - 2020
- [j10]Mirco Nanni, Gennady L. Andrienko, Albert-László Barabási, Chiara Boldrini, Francesco Bonchi, Ciro Cattuto, Francesca Chiaromonte, Giovanni Comandè, Marco Conti, Mark Coté, Frank Dignum, Virginia Dignum, Josep Domingo-Ferrer, Paolo Ferragina, Fosca Giannotti, Riccardo Guidotti, Dirk Helbing, Kimmo Kaski, János Kertész, Sune Lehmann, Bruno Lepri, Paul Lukowicz, Stan Matwin, David Megías, Anna Monreale, Katharina Morik, Nuria Oliver, Andrea Passarella, Andrea Passerini, Dino Pedreschi, Alex Pentland, Fabio Pianesi, Francesca Pratesi, Salvatore Rinzivillo, Salvatore Ruggieri, Arno Siebes, Vicenç Torra, Roberto Trasarti, Jeroen van den Hoven, Alessandro Vespignani:
Give more data, awareness and control to individual citizens, and they will help COVID-19 containment. Trans. Data Priv. 13(1): 61-66 (2020) - [c40]Riccardo Guidotti, Anna Monreale, Stan Matwin, Dino Pedreschi:
Explaining Image Classifiers Generating Exemplars and Counter-Exemplars from Latent Representations. AAAI 2020: 13665-13668 - [c39]Riccardo Guidotti, Stefano Viotto:
Interpretable Next Basket Prediction Boosted with Representative Recipes. CogMI 2020: 62-71 - [c38]Riccardo Guidotti, Anna Monreale, Francesco Spinnato, Dino Pedreschi, Fosca Giannotti:
Explaining Any Time Series Classifier. CogMI 2020: 167-176 - [c37]Orestis Lampridis, Riccardo Guidotti, Salvatore Ruggieri:
Explaining Sentiment Classification with Synthetic Exemplars and Counter-Exemplars. DS 2020: 357-373 - [c36]Agnese Bonavita, Riccardo Guidotti, Mirco Nanni:
Self-Adapting Trajectory Segmentation. EDBT/ICDT Workshops 2020 - [c35]Riccardo Guidotti, Mirco Nanni, Francesca Sbolgi:
Data-Driven Location Annotation for Fleet Mobility Modeling. EDBT/ICDT Workshops 2020 - [c34]Riccardo Guidotti, Anna Monreale:
Data-Agnostic Local Neighborhood Generation. ICDM 2020: 1040-1045 - [c33]Riccardo Guidotti, Mirco Nanni:
Crash Prediction and Risk Assessment with Individual Mobility Networks. MDM 2020: 89-98 - [c32]Riccardo Guidotti, Mirco Nanni, Fosca Giannotti, Dino Pedreschi, Simone Bertoli, Biagio Speciale, Hillel Rapoport:
Measuring Immigrants Adoption of Natives Shopping Consumption with Machine Learning. ECML/PKDD (5) 2020: 369-385 - [c31]Riccardo Guidotti:
Explaining Explanation Methods. BIRDS@SIGIR 2020: 6-13 - [p2]Cecilia Panigutti, Riccardo Guidotti, Anna Monreale, Dino Pedreschi:
Explaining Multi-label Black-Box Classifiers for Health Applications. Precision Health and Medicine 2020: 97-110 - [e5]Emil Sekerinski, Nelma Moreira, José N. Oliveira, Daniel Ratiu, Riccardo Guidotti, Marie Farrell, Matt Luckcuck, Diego Marmsoler, José Creissac Campos, Troy Astarte, Laure Gonnord, Antonio Cerone, Luis Couto, Brijesh Dongol, Martin Kutrib, Pedro Monteiro, David Delmas:
Formal Methods. FM 2019 International Workshops - Porto, Portugal, October 7-11, 2019, Revised Selected Papers, Part I. Lecture Notes in Computer Science 12232, Springer 2020, ISBN 978-3-030-54993-0 [contents] - [e4]Emil Sekerinski, Nelma Moreira, José N. Oliveira, Daniel Ratiu, Riccardo Guidotti, Marie Farrell, Matt Luckcuck, Diego Marmsoler, José Creissac Campos, Troy Astarte, Laure Gonnord, Antonio Cerone, Luis Couto, Brijesh Dongol, Martin Kutrib, Pedro Monteiro, David Delmas:
Formal Methods. FM 2019 International Workshops - Porto, Portugal, October 7-11, 2019, Revised Selected Papers, Part II. Lecture Notes in Computer Science 12233, Springer 2020, ISBN 978-3-030-54996-1 [contents] - [e3]Irena Koprinska, Michael Kamp, Annalisa Appice, Corrado Loglisci, Luiza Antonie, Albrecht Zimmermann, Riccardo Guidotti, Özlem Özgöbek, Rita P. Ribeiro, Ricard Gavaldà, João Gama, Linara Adilova, Yamuna Krishnamurthy, Pedro M. Ferreira, Donato Malerba, Ibéria Medeiros, Michelangelo Ceci, Giuseppe Manco, Elio Masciari, Zbigniew W. Ras, Peter Christen, Eirini Ntoutsi, Erich Schubert, Arthur Zimek, Anna Monreale, Przemyslaw Biecek, Salvatore Rinzivillo, Benjamin Kille, Andreas Lommatzsch, Jon Atle Gulla:
ECML PKDD 2020 Workshops - Workshops of the European Conference on Machine Learning and Knowledge Discovery in Databases (ECML PKDD 2020): SoGood 2020, PDFL 2020, MLCS 2020, NFMCP 2020, DINA 2020, EDML 2020, XKDD 2020 and INRA 2020, Ghent, Belgium, September 14-18, 2020, Proceedings. Communications in Computer and Information Science 1323, Springer 2020, ISBN 978-3-030-65964-6 [contents] - [i8]Riccardo Guidotti, Anna Monreale, Stan Matwin, Dino Pedreschi:
Black Box Explanation by Learning Image Exemplars in the Latent Feature Space. CoRR abs/2002.03746 (2020) - [i7]