191 citations · 372 across the 19 of their papers we have counts for
23 papers
Bounded-Abstention Multi-horizon Time-series Forecasting
Luca Stradiotti, Laurens Devos, Anna Monreale +2
Multi-horizon time-series forecasting involves simultaneously making predictions for a consecutive sequence of subsequent time steps. This task arises in many application domains,…
Causal Synthetic Data Generation in Recruitment
Andrea Iommi, Antonio Mastropietro, Riccardo Guidotti +2
The importance of Synthetic Data Generation (SDG) has increased significantly in domains where data quality is poor or access is limited due to privacy and regulatory constraints.…
An Interpretable Data-Driven Unsupervised Approach for the Prevention of Forgotten Items
Luca Corbucci, Javier Alejandro Borges Legrottaglie, Francesco Spinnato +2
Accurately identifying items forgotten during a supermarket visit and providing clear, interpretable explanations for recommending them remains an underexplored problem within the…
Multimodal Coordinated Online Behavior: Trade-offs and Strategies
Lorenzo Mannocci, Stefano Cresci, Matteo Magnani +2
Coordinated online behavior, which spans from beneficial collective actions to harmful manipulation such as disinformation campaigns, has become a key focus in digital ecosystem an…
Improving Regulatory Oversight in Online Content Moderation
Benedetta Tessa, Denise Amram, Anna Monreale +1
The European Union introduced the Digital Services Act (DSA) to address the risks associated with digital platforms and promote a safer online environment. However, despite the pot…
FeDa4Fair: Client-Level Federated Datasets for Fairness Evaluation
Xenia Heilmann, Luca Corbucci, Mattia Cerrato +1
Federated Learning (FL) enables collaborative training while preserving privacy, yet it introduces a critical challenge: the "illusion of fairness''. A global model, usually evalua…
Workshop Scientific HPC in the pre-Exascale era (part of ITADATA 2024) Proceedings
Nicola Bena, Claudia Diamantini, Michela Natilli +10
The proceedings of Workshop Scientific HPC in the pre-Exascale era (SHPC), held in Pisa, Italy, September 18, 2024, are part of 3rd Italian Conference on Big Data and Data Science…
Talking Back -- human input and explanations to interactive AI systems
Alan Dix, Tommaso Turchi, Ben Wilson +2
While XAI focuses on providing AI explanations to humans, can the reverse - humans explaining their judgments to AI - foster richer, synergistic human-AI systems? This paper explor…
Explainable AI in Time-Sensitive Scenarios: Prefetched Offline Explanation Model
Fabio Michele Russo, Carlo Metta, Anna Monreale +2
As predictive machine learning models become increasingly adopted and advanced, their role has evolved from merely predicting outcomes to actively shaping them. This evolution has…
Proceedings of the 3rd Italian Conference on Big Data and Data Science (ITADATA2024)
Nicola Bena, Claudia Diamantini, Michela Natilli +6
Proceedings of the 3rd Italian Conference on Big Data and Data Science (ITADATA2024), held in Pisa, Italy, September 17-19, 2024. The Italian Conference on Big Data and Data Scienc…
Detection and Characterization of Coordinated Online Behavior: A Survey
Lorenzo Mannocci, Michele Mazza, Anna Monreale +2
Coordination is a fundamental aspect of life. The advent of social media has made it integral also to online human interactions, such as those that characterize thriving online com…
PUFFLE: Balancing Privacy, Utility, and Fairness in Federated Learning
Luca Corbucci, Mikko A Heikkila, David Solans Noguero +2
Training and deploying Machine Learning models that simultaneously adhere to principles of fairness and privacy while ensuring good utility poses a significant challenge. The inter…
Fast, Interpretable, and Deterministic Time Series Classification With a Bag-of-Receptive-Fields
Francesco Spinnato, Riccardo Guidotti, Anna Monreale +1
The current trend in the literature on Time Series Classification is to develop increasingly accurate algorithms by combining multiple models in ensemble hybrids, representing time…
Explainable Authorship Identification in Cultural Heritage Applications: Analysis of a New Perspective
Mattia Setzu, Silvia Corbara, Anna Monreale +2
While a substantial amount of work has recently been devoted to enhance the performance of computational Authorship Identification (AId) systems, little to no attention has been pa…
MulBot: Unsupervised Bot Detection Based on Multivariate Time Series
Lorenzo Mannocci, Stefano Cresci, Anna Monreale +2
Online social networks are actively involved in the removal of malicious social bots due to their role in the spread of low quality information. However, most of the existing bot d…
Human Response to an AI-Based Decision Support System: A User Study on the Effects of Accuracy and Bias
David Solans, Andrea Beretta, Manuel Portela +2
Artificial Intelligence (AI) is increasingly used to build Decision Support Systems (DSS) across many domains. This paper describes a series of experiments designed to observe huma…
Making Sense of Moodle Log Data
Daniela Rotelli, Anna Monreale
Research is constantly engaged in finding more productive and powerful ways to support quality learning and teaching. However, although researchers and data scientists try to analy…
GLocalX -- From Local to Global Explanations of Black Box AI Models
Mattia Setzu, Riccardo Guidotti, Anna Monreale +3
Artificial Intelligence (AI) has come to prominence as one of the major components of our society, with applications in most aspects of our lives. In this field, complex and highly…
Give more data, awareness and control to individual citizens, and they will help COVID-19 containment
Mirco Nanni, Gennady Andrienko, Albert-László Barabási +36
The rapid dynamics of COVID-19 calls for quick and effective tracking of virus transmission chains and early detection of outbreaks, especially in the phase 2 of the pandemic, when…
Black Box Explanation by Learning Image Exemplars in the Latent Feature Space
Riccardo Guidotti, Anna Monreale, Stan Matwin +1
We present an approach to explain the decisions of black box models for image classification. While using the black box to label images, our explanation method exploits the latent…
Open the Black Box Data-Driven Explanation of Black Box Decision Systems
Dino Pedreschi, Fosca Giannotti, Riccardo Guidotti +4
Black box systems for automated decision making, often based on machine learning over (big) data, map a user's features into a class or a score without exposing the reasons why. Th…
Local Rule-Based Explanations of Black Box Decision Systems
Riccardo Guidotti, Anna Monreale, Salvatore Ruggieri +3
The recent years have witnessed the rise of accurate but obscure decision systems which hide the logic of their internal decision processes to the users. The lack of explanations f…
A Survey Of Methods For Explaining Black Box Models
Riccardo Guidotti, Anna Monreale, Salvatore Ruggieri +3
In the last years many accurate decision support systems have been constructed as black boxes, that is as systems that hide their internal logic to the user. This lack of explanati…