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20122026
most citedA Classification for Community Discovery Methods in Complex Networks

297 citations · 1.5k across the 35 of their papers we have counts for

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6 papers · 1 filter

cs.AI2023★ 9 cited

Human-AI Coevolution

Dino Pedreschi, Luca Pappalardo, Emanuele Ferragina +14

Human-AI coevolution, defined as a process in which humans and AI algorithms continuously influence each other, increasingly characterises our society, but is understudied in artif…

cs.AI2023★ 14 cited

Boosting Synthetic Data Generation with Effective Nonlinear Causal Discovery

Martina Cinquini, Fosca Giannotti, Riccardo Guidotti

Synthetic data generation has been widely adopted in software testing, data privacy, imbalanced learning, and artificial intelligence explanation. In all such contexts, it is cruci…

cs.AI2021

Understanding peacefulness through the world news

Vasiliki Voukelatou, Ioanna Miliou, Fosca Giannotti +1

Peacefulness is a principal dimension of well-being and is the way out of inequity and violence. Thus, its measurement has drawn the attention of researchers, policymakers, and pea…

cs.AI2021★ 55 cited

Benchmarking and Survey of Explanation Methods for Black Box Models

Francesco Bodria, Fosca Giannotti, Riccardo Guidotti +3

The widespread adoption of black-box models in Artificial Intelligence has enhanced the need for explanation methods to reveal how these obscure models reach specific decisions. Re…

cs.AI2018★ 35 cited

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…

cs.AI2018★ 191 cited

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…