Riccardo Guidotti

Orcid: 0000-0002-2827-7613

According to our database1, Riccardo Guidotti authored at least 129 papers between 2014 and 2024.

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Bibliography

2024
The role of encodings and distance metrics for the quantum nearest neighbor.
Quantum Mach. Intell., December, 2024

Quantum subroutine for variance estimation: algorithmic design and applications.
Quantum Mach. Intell., December, 2024

Explaining Siamese networks in few-shot learning.
Mach. Learn., October, 2024

Stable and actionable explanations of black-box models through factual and counterfactual rules.
Data Min. Knowl. Discov., September, 2024

Counterfactual explanations and how to find them: literature review and benchmarking.
Data Min. Knowl. Discov., September, 2024

Solving imbalanced learning with outlier detection and features reduction.
Mach. Learn., July, 2024

Understanding Any Time Series Classifier with a Subsequence-based Explainer.
ACM Trans. Knowl. Discov. Data, February, 2024

Quantum clustering with k-Means: A hybrid approach.
Theor. Comput. Sci., 2024

Explainable Artificial Intelligence (XAI) 2.0: A manifesto of open challenges and interdisciplinary research directions.
Inf. Fusion, 2024

Drifting explanations in continual learning.
Neurocomputing, 2024

Bridging the Gap in Hybrid Decision-Making Systems.
CoRR, 2024

Fast, Interpretable, and Deterministic Time Series Classification With a Bag-of-Receptive-Fields.
IEEE Access, 2024

Counterfactual and Prototypical Explanations for Tabular Data via Interpretable Latent Space.
IEEE Access, 2024

Causality-Aware Local Interpretable Model-Agnostic Explanations.
Proceedings of the Explainable Artificial Intelligence, 2024

Data-Agnostic Pivotal Instances Selection for Decision-Making Models.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2024

A Frank System for Co-Evolutionary Hybrid Decision-Making.
Proceedings of the Advances in Intelligent Data Analysis XXII, 2024

FLocalX - Local to Global Fuzzy Explanations for Black Box Classifiers.
Proceedings of the Advances in Intelligent Data Analysis XXII, 2024

Social Bias Probing: Fairness Benchmarking for Language Models.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

A Shape-Based Map Matching Approach for Geographic Transferability of Discriminative Subtrajectories.
Proceedings of the Workshops of the EDBT/ICDT 2024 Joint Conference co-located with the EDBT/ICDT 2024 Joint Conference, 2024

Requirements of eXplainable AI in Algorithmic Hiring.
Proceedings of the 1st Workshop on AI bias: Measurements, 2024

Generative Model for Decision Trees.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Explaining short text classification with diverse synthetic exemplars and counter-exemplars.
Mach. Learn., November, 2023

Explainable Artificial Intelligence (XAI): What we know and what is left to attain Trustworthy Artificial Intelligence.
Inf. Fusion, November, 2023

Benchmarking and survey of explanation methods for black box models.
Data Min. Knowl. Discov., September, 2023

An Explanation that LASTS: Understanding Any Time Series Classifier.
ERCIM News, 2023

A Bag of Receptive Fields for Time Series Extrinsic Predictions.
CoRR, 2023

Explaining Black-Boxes in Federated Learning.
Proceedings of the Explainable Artificial Intelligence, 2023

Handling Missing Values in Local Post-hoc Explainability.
Proceedings of the Explainable Artificial Intelligence, 2023


Geolet: An Interpretable Model for Trajectory Classification.
Proceedings of the Advances in Intelligent Data Analysis XXI, 2023

The Trajectory Interval Forest Classifier for Trajectory Classification.
Proceedings of the 31st ACM International Conference on Advances in Geographic Information Systems, 2023

Quantum Feature Selection with Variance Estimation.
Proceedings of the 31st European Symposium on Artificial Neural Networks, 2023

A Protocol for Continual Explanation of SHAP.
Proceedings of the 31st European Symposium on Artificial Neural Networks, 2023

Text to Time Series Representations: Towards Interpretable Predictive Models.
Proceedings of the Discovery Science - 26th International Conference, 2023

GenFair: A Genetic Fairness-Enhancing Data Generation Framework.
Proceedings of the Discovery Science - 26th International Conference, 2023

Interpretable Data Partitioning Through Tree-Based Clustering Methods.
Proceedings of the Discovery Science - 26th International Conference, 2023

Applied Data Science for Leasing Score Prediction.
Proceedings of the IEEE International Conference on Big Data, 2023

2022
Exploiting auto-encoders for explaining black-box classifiers.
Intelligenza Artificiale, 2022

City indicators for geographical transfer learning: an application to crash prediction.
GeoInformatica, 2022

Individual and collective stop-based adaptive trajectory segmentation.
GeoInformatica, 2022

CALIME: Causality-Aware Local Interpretable Model-Agnostic Explanations.
CoRR, 2022

Explainable AI for Time Series Classification: A Review, Taxonomy and Research Directions.
IEEE Access, 2022

Explaining Black Box with Visual Exploration of Latent Space.
Proceedings of the 24th Eurographics Conference on Visualization, 2022

Effect of Different Encodings and Distance Functions on Quantum Instance-Based Classifiers.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2022

Bias Discovery within Human Raters: A Case Study of the Jigsaw Dataset.
Proceedings of the 1st Workshop on Perspectivist Approaches to NLPerspectives@LREC 2022, 2022

Clustering Classical Data with Quantum k-Means.
Proceedings of the 23rd Italian Conference on Theoretical Computer Science, 2022

Exemplars and Counterexemplars Explanations for Skin Lesion Classifiers.
Proceedings of the HHAI 2022: Augmenting Human Intellect, 2022

Uncovering Student Temporal Learning Patterns.
Proceedings of the Educating for a New Future: Making Sense of Technology-Enhanced Learning Adoption, 2022

Transparent Latent Space Counterfactual Explanations for Tabular Data.
Proceedings of the 9th IEEE International Conference on Data Science and Advanced Analytics, 2022

Explaining Crash Predictions on Multivariate Time Series Data.
Proceedings of the Discovery Science - 25th International Conference, 2022

Explaining Siamese Networks in Few-Shot Learning for Audio Data.
Proceedings of the Discovery Science - 25th International Conference, 2022

Interpretable Latent Space to Enable Counterfactual Explanations.
Proceedings of the Discovery Science - 25th International Conference, 2022

Investigating Debiasing Effects on Classification and Explainability.
Proceedings of the AIES '22: AAAI/ACM Conference on AI, Ethics, and Society, Oxford, United Kingdom, May 19, 2022

A Modularized Framework for Explaining Black Box Classifiers for Text Data.
Proceedings of the 35th Canadian Conference on Artificial Intelligence, Toronto, Ontario, 2022

2021
Correction to: Human migration: the big data perspective.
Int. J. Data Sci. Anal., 2021

Human migration: the big data perspective.
Int. J. Data Sci. Anal., 2021

(So) Big Data and the transformation of the city.
Int. J. Data Sci. Anal., 2021

Matrix Profile-Based Interpretable Time Series Classifier.
Frontiers Artif. Intell., 2021

Give more data, awareness and control to individual citizens, and they will help COVID-19 containment.
Ethics Inf. Technol., 2021

Explainable Deep Image Classifiers for Skin Lesion Diagnosis.
CoRR, 2021

GLocalX - From Local to Global Explanations of Black Box AI Models.
Artif. Intell., 2021

Evaluating local explanation methods on ground truth.
Artif. Intell., 2021

Exemplars and Counterexemplars Explanations for Image Classifiers, Targeting Skin Lesion Labeling.
Proceedings of the IEEE Symposium on Computers and Communications, 2021

City Indicators for Mobility Data Mining.
Proceedings of the Workshops of the EDBT/ICDT 2021 Joint Conference, 2021

Ensemble of Counterfactual Explainers.
Proceedings of the Discovery Science - 24th International Conference, 2021

Deriving a Single Interpretable Model by Merging Tree-Based Classifiers.
Proceedings of the Discovery Science - 24th International Conference, 2021

FairShades: Fairness Auditing via Explainability in Abusive Language Detection Systems.
Proceedings of the Third IEEE International Conference on Cognitive Machine Intelligence, 2021

Boosting Synthetic Data Generation with Effective Nonlinear Causal Discovery.
Proceedings of the Third IEEE International Conference on Cognitive Machine Intelligence, 2021

Designing Shapelets for Interpretable Data-Agnostic Classification.
Proceedings of the AIES '21: AAAI/ACM Conference on AI, 2021

A modularized framework for explaining hierarchical attention networks on text classifiers.
Proceedings of the 34th Canadian Conference on Artificial Intelligence, 2021

2020
Explaining Multi-label Black-Box Classifiers for Health Applications.
Proceedings of the Precision Health and Medicine - A Digital Revolution in Healthcare, 2020

Give more data, awareness and control to individual citizens, and they will help COVID-19 containment.
CoRR, 2020

Explaining Explanation Methods.
Proceedings of the First Workshop on Bridging the Gap between Information Science, Information Retrieval and Data Science (BIRDS 2020) co-located with 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2020), Xi'an, China (online only), July 30th,, 2020

Measuring Immigrants Adoption of Natives Shopping Consumption with Machine Learning.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Applied Data Science and Demo Track, 2020

Crash Prediction and Risk Assessment with Individual Mobility Networks.
Proceedings of the 21st IEEE International Conference on Mobile Data Management, 2020

Data-Agnostic Local Neighborhood Generation.
Proceedings of the 20th IEEE International Conference on Data Mining, 2020

Data-Driven Location Annotation for Fleet Mobility Modeling.
Proceedings of the Workshops of the EDBT/ICDT 2020 Joint Conference, 2020

Self-Adapting Trajectory Segmentation.
Proceedings of the Workshops of the EDBT/ICDT 2020 Joint Conference, 2020

Explaining Sentiment Classification with Synthetic Exemplars and Counter-Exemplars.
Proceedings of the Discovery Science - 23rd International Conference, 2020

Interpretable Next Basket Prediction Boosted with Representative Recipes.
Proceedings of the 2nd IEEE International Conference on Cognitive Machine Intelligence, 2020

Explaining Any Time Series Classifier.
Proceedings of the 2nd IEEE International Conference on Cognitive Machine Intelligence, 2020

Explaining Image Classifiers Generating Exemplars and Counter-Exemplars from Latent Representations.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Personalized Market Basket Prediction with Temporal Annotated Recurring Sequences.
IEEE Trans. Knowl. Data Eng., 2019

The italian music superdiversity - Geography, emotion and language: one resource to find them, one resource to rule them all.
Multim. Tools Appl., 2019

Factual and Counterfactual Explanations for Black Box Decision Making.
IEEE Intell. Syst., 2019

The AI Black Box Explanation Problem.
ERCIM News, 2019

A Survey of Methods for Explaining Black Box Models.
ACM Comput. Surv., 2019

Global Explanations with Local Scoring.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019

Black Box Explanation by Learning Image Exemplars in the Latent Feature Space.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019

Investigating Neighborhood Generation Methods for Explanations of Obscure Image Classifiers.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2019

On The Stability of Interpretable Models.
Proceedings of the International Joint Conference on Neural Networks, 2019

"Know Thyself" How Personal Music Tastes Shape the Last.Fm Online Social Network.
Proceedings of the Formal Methods. FM 2019 International Workshops, 2019

Meaningful Explanations of Black Box AI Decision Systems.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
Discovering temporal regularities in retail customers' shopping behavior.
EPJ Data Sci., 2018

Assessing the Stability of Interpretable Models.
CoRR, 2018

Open the Black Box Data-Driven Explanation of Black Box Decision Systems.
CoRR, 2018

Local Rule-Based Explanations of Black Box Decision Systems.
CoRR, 2018

A Survey Of Methods For Explaining Black Box Models.
CoRR, 2018

Explaining Successful Docker Images Using Pattern Mining Analysis.
Proceedings of the Software Technologies: Applications and Foundations, 2018

Privacy Risk for Individual Basket Patterns.
Proceedings of the ECML PKDD 2018 Workshops, 2018

Exploring Students Eating Habits Through Individual Profiling and Clustering Analysis.
Proceedings of the ECML PKDD 2018 Workshops, 2018

Helping Your Docker Images to Spread Based on Explainable Models.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2018

Learning Data Mining.
Proceedings of the 5th IEEE International Conference on Data Science and Advanced Analytics, 2018

2017
Personal Data Analytics: Capturing Human Behavior to Improve Self-Awareness and Personal Services through Individual and Collective Knowledge.
PhD thesis, 2017

MyWay: Location prediction via mobility profiling.
Inf. Syst., 2017

Never drive alone: Boosting carpooling with network analysis.
Inf. Syst., 2017

Next Basket Prediction using Recurring Sequential Patterns.
CoRR, 2017

Clustering Individual Transactional Data for Masses of Users.
Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 2017

Market Basket Prediction Using User-Centric Temporal Annotated Recurring Sequences.
Proceedings of the 2017 IEEE International Conference on Data Mining, 2017

The Fractal Dimension of Music: Geography, Popularity and Sentiment Analysis.
Proceedings of the Smart Objects and Technologies for Social Good, 2017

Recognizing Residents and Tourists with Retail Data Using Shopping Profiles.
Proceedings of the Smart Objects and Technologies for Social Good, 2017

On the Equivalence Between Community Discovery and Clustering.
Proceedings of the Smart Objects and Technologies for Social Good, 2017

There's a Path for Everyone: A Data-Driven Personal Model Reproducing Mobility Agendas.
Proceedings of the 2017 IEEE International Conference on Data Science and Advanced Analytics, 2017

2016
ICON Loop Carpooling Show Case.
Proceedings of the Data Mining and Constraint Programming, 2016

A supervised approach for intra-/inter-community interaction prediction in dynamic social networks.
Soc. Netw. Anal. Min., 2016

Unveiling mobility complexity through complex network analysis.
Soc. Netw. Anal. Min., 2016

Audio Ergo Sum - A Personal Data Model for Musical Preferences.
Proceedings of the Software Technologies: Applications and Foundations, 2016

Going Beyond GDP to Nowcast Well-Being Using Retail Market Data.
Proceedings of the Advances in Network Science, 2016

Where Is My Next Friend? Recommending Enjoyable Profiles in Location Based Services.
Proceedings of the Complex Networks VII, 2016

2015
Towards a Boosted Route Planner Using Individual Mobility Models.
Proceedings of the Software Engineering and Formal Methods, 2015

Mobility Mining for Journey Planning in Rome.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2015

Social or Green? A Data-Driven Approach for More Enjoyable Carpooling.
Proceedings of the IEEE 18th International Conference on Intelligent Transportation Systems, 2015

Managing travels with PETRA: The Rome use case.
Proceedings of the 31st IEEE International Conference on Data Engineering Workshops, 2015

Towards user-centric data management: individual mobility analytics for collective services.
Proceedings of the 4th ACM SIGSPATIAL International Workshop on Mobile Geographic Information Systems, 2015

TOSCA: two-steps clustering algorithm for personal locations detection.
Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems, 2015

Behavioral entropy and profitability in retail.
Proceedings of the 2015 IEEE International Conference on Data Science and Advanced Analytics, 2015

Find Your Way Back: Mobility Profile Mining with Constraints.
Proceedings of the Principles and Practice of Constraint Programming, 2015

Interaction Prediction in Dynamic Networks exploiting Community Discovery.
Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, 2015

2014
Retrieving Points of Interest from Human Systematic Movements.
Proceedings of the Software Engineering and Formal Methods, 2014


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