RUGGIERI, SALVATORE
RUGGIERI, SALVATORE
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
Bias discovery within human raters: a case study of the Jigsaw dataset
2022 Manerba Marchiori, M.; Guidotti, R.; Passaro, L.; Ruggieri, S.
Explaining short text classification with diverse synthetic exemplars and counter-exemplars
2022 Lampridis, O; State, L; Guidotti, R; Ruggieri, S
Stable and actionable explanations of black-box models through factual and counterfactual rules
2022 Guidotti, R.; Monreale, A.; Ruggieri, S.; Naretto, F.; Turini, F.; Pedreschi, D.; Giannotti, F.
Ensemble of counterfactual explainers
2021 Guidotti, R.; Ruggieri, S.
Causal inference for social discrimination reasoning
2020 Qureshi B.; Kamiran F.; Karim A.; Ruggieri S.; Pedreschi D.
A survey of methods for explaining black box models
2019 Guidotti R.; Monreale A.; Ruggieri S.; Turini F.; Giannotti F.; Pedreschi D.
On the stability of interpretable models
2019 Guidotti, R; Ruggieri, S
Assessing the stability of interpretable models
2018 Guidotti, R; Ruggieri, S
How data mining and machine learning evolved from relational data base to data science
2018 Amato G.; Candela L.; Castelli D.; Esuli A.; Falchi F.; Gennaro C.; Giannotti F.; Monreale A.; Nanni M.; Pagano P.; Pappalardo L.; Pedreschi D.; Pratesi F.; Rabitti F.; Rinzivillo S.; Rossetti G.; Ruggieri S.; Sebastiani F.; Tesconi M.
Local rule-based explanations of black box decision systems
2018 Guidotti R.; Monreale A.; Ruggieri S.; Pedreschi D.; Turini F.; Giannotti F.
Open the black box data-driven explanation of black box decision systems
2018 Pedreschi D.; Giannotti F.; Guidotti R.; Monreale A.; Pappalardo L.; Ruggieri S.; Turini F.
Efficiently clustering very large attributed graphs
2017 Baroni A.; Conte A.; Patrignani M.; Ruggieri S.
Big data research in Italy: a perspective
2016 Bergamaschi S.; Carlini E.; Ceci M.; Furletti B.; Giannotti F.; Malerba D.; Mezzanzanica M.; Monreale A.; Pasi G.; Pedreschi D.; Perego R.; Ruggieri S.
A multidisciplinary survey on discrimination analysis
2014 Romei, A; Ruggieri, S
Decision tree building on multi-core using FastFlow
2014 Aldinucci M.; Ruggieri S.; Torquati M.
Data anonimity meets non-discrimination
2013 Ruggieri, S
Discrimination Data Analysis: A Multi-disciplinary Bibliography
2013 Romei A.; Ruggieri S.
Discrimination discovery in scientific project evaluation: a case study
2013 Romei A.; Ruggieri S.; Turini F.
Learning from polyhedral sets
2013 Ruggieri, S
The discovery of discrimination
2013 Pedreschi, D; Ruggieri, S; Turini, F
| Titolo | Data di pubblicazione | Autore(i) | File |
|---|---|---|---|
| Bias discovery within human raters: a case study of the Jigsaw dataset | 1-gen-2022 | Manerba Marchiori, M.; Guidotti, R.; Passaro, L.; Ruggieri, S. | |
| Explaining short text classification with diverse synthetic exemplars and counter-exemplars | 1-gen-2022 | Lampridis, O; State, L; Guidotti, R; Ruggieri, S | |
| Stable and actionable explanations of black-box models through factual and counterfactual rules | 1-gen-2022 | Guidotti, R.; Monreale, A.; Ruggieri, S.; Naretto, F.; Turini, F.; Pedreschi, D.; Giannotti, F. | |
| Ensemble of counterfactual explainers | 1-gen-2021 | Guidotti, R.; Ruggieri, S. | |
| Causal inference for social discrimination reasoning | 1-gen-2020 | Qureshi B.; Kamiran F.; Karim A.; Ruggieri S.; Pedreschi D. | |
| A survey of methods for explaining black box models | 1-gen-2019 | Guidotti R.; Monreale A.; Ruggieri S.; Turini F.; Giannotti F.; Pedreschi D. | |
| On the stability of interpretable models | 1-gen-2019 | Guidotti, R; Ruggieri, S | |
| Assessing the stability of interpretable models | 1-gen-2018 | Guidotti, R; Ruggieri, S | |
| How data mining and machine learning evolved from relational data base to data science | 1-gen-2018 | Amato G.; Candela L.; Castelli D.; Esuli A.; Falchi F.; Gennaro C.; Giannotti F.; Monreale A.; Nanni M.; Pagano P.; Pappalardo L.; Pedreschi D.; Pratesi F.; Rabitti F.; Rinzivillo S.; Rossetti G.; Ruggieri S.; Sebastiani F.; Tesconi M. | |
| Local rule-based explanations of black box decision systems | 1-gen-2018 | Guidotti R.; Monreale A.; Ruggieri S.; Pedreschi D.; Turini F.; Giannotti F. | |
| Open the black box data-driven explanation of black box decision systems | 1-gen-2018 | Pedreschi D.; Giannotti F.; Guidotti R.; Monreale A.; Pappalardo L.; Ruggieri S.; Turini F. | |
| Efficiently clustering very large attributed graphs | 1-gen-2017 | Baroni A.; Conte A.; Patrignani M.; Ruggieri S. | |
| Big data research in Italy: a perspective | 1-gen-2016 | Bergamaschi S.; Carlini E.; Ceci M.; Furletti B.; Giannotti F.; Malerba D.; Mezzanzanica M.; Monreale A.; Pasi G.; Pedreschi D.; Perego R.; Ruggieri S. | |
| A multidisciplinary survey on discrimination analysis | 1-gen-2014 | Romei, A; Ruggieri, S | |
| Decision tree building on multi-core using FastFlow | 1-gen-2014 | Aldinucci M.; Ruggieri S.; Torquati M. | |
| Data anonimity meets non-discrimination | 1-gen-2013 | Ruggieri, S | |
| Discrimination Data Analysis: A Multi-disciplinary Bibliography | 1-gen-2013 | Romei A.; Ruggieri S. | |
| Discrimination discovery in scientific project evaluation: a case study | 1-gen-2013 | Romei A.; Ruggieri S.; Turini F. | |
| Learning from polyhedral sets | 1-gen-2013 | Ruggieri, S | |
| The discovery of discrimination | 1-gen-2013 | Pedreschi, D; Ruggieri, S; Turini, F |