MILANO, MICHELA
MILANO, MICHELA
DIPARTIMENTO DI INFORMATICA - SCIENZA E INGEGNERIA
Docenti di ruolo di Ia fascia
A geometric framework for fairness
2023 Maggio A.; Giuliani L.; Calegari R.; Lombardi M.; Milano M.
Assessing and Enforcing Fairness in the AI Lifecycle
2023 Calegari R.; Castane G.G.; Milano M.; O'Sullivan B.
FAiRDAS: Fairness-Aware Ranking as Dynamic Abstract System
2023 Misino E.; Calegari R.; Lombardi M.; Milano M.
Preface: Fairness and Bias in AI: Insights from AEQUITAS 2023
2023 Calegari R.; Aler A.; Gabriel T.; Castane G.; Dignum V.; Milano M.
Proceedings of the 1st Workshop on Fairness and Bias in AI, AEQUITAS 2023 co-located with 26th European Conference on Artificial Intelligence (ECAI 2023)
2023 Roberta Calegari, Andrea Aler Tubella, Gabriel González Castañe, Virginia Dignum, Michela Milano
Towards Symbiotic Creativity: A Methodological Approach to Compare Human and AI Robotic Dance Creations
2023 De Filippo, Allegra; Giuliani, Luca; Mancini, Eleonora; Borghesi, Andrea; Mello, Paola; Milano, Michela
A Multi-modal Perspective for the Artistic Evaluation of Robotic Dance Performances
2022 Luca Giuliani, Allegra De Filippo, Andrea Borghesi, Paola Mello, Michela Milano
Anomaly Detection and Anticipation in High Performance Computing Systems
2022 Borghesi A.; Molan M.; Milano M.; Bartolini A.
Do You Like Dancing Robots? AI Can Tell You Why
2022 De Filippo A.; Mello P.; Milano M.
HADA: An automated tool for hardware dimensioning of AI applications
2022 De Filippo, A; Borghesi, A; Boscarino, A; Milano, M
Informed Deep Learning for Epidemics Forecasting
2022 Federico Baldo, Michele Iannello, Michele Lombardi, Michela Milano
An Analysis of Regularized Approaches for Constrained Machine Learning
2021 Lombardi, Michele; Baldo, Federico; Borghesi, Andrea; Milano, Michela
Injecting Domain Knowledge in Neural Networks: A Controlled Experiment on a Constrained Problem
2021 Silvestri M.; Lombardi M.; Milano M.
Integrated Offline and Online Decision Making under Uncertainty
2021 De Filippo, Allegra; Lombardi, Michele; Milano, Michela
Teaching the Old Dog New Tricks: Supervised Learning with Constraints
2021 Fabrizio Detassis, Michele Lombardi, Michela Milano
Combining learning and optimization for transprecision computing
2020 Borghesi, Andrea; Tagliavini, Giuseppe; Lombardi, Michele; Benini, Luca; Milano, Michela
Hybrid offline/online optimization under uncertainty
2020 De Filippo A.; Lombardi M.; Milano M.
Injecting domain knowledge in neural networks: A controlled experiment on a constrained problem
2020 Silvestri M.; Lombardi M.; Milano M.
Injective Domain Knowledge in Neural Networks for Transprecision Computing
2020 Andrea Borghesi, Federico Baldo, Michele Lombardi, Michela Milano
Teaching the old dog new tricks: Supervised learning with constraints
2020 Detassis F.; Lombardi M.; Milano M.
| Titolo | Autore(i) | Anno | Periodico | Editore | Tipo | File |
|---|---|---|---|---|---|---|
| A geometric framework for fairness | Maggio A.; Giuliani L.; Calegari R.; Lombardi M.; Milano M. | 2023-01-01 | - | CEUR-WS | 4.01 Contributo in Atti di convegno | paper9.pdf |
| Assessing and Enforcing Fairness in the AI Lifecycle | Calegari R.; Castane G.G.; Milano M.; O'Sullivan B. | 2023-01-01 | IJCAI | International Joint Conferences on Artificial Intelligence | 4.01 Contributo in Atti di convegno | 0735.pdf |
| FAiRDAS: Fairness-Aware Ranking as Dynamic Abstract System | Misino E.; Calegari R.; Lombardi M.; Milano M. | 2023-01-01 | - | CEUR-WS | 4.01 Contributo in Atti di convegno | paper5.pdf |
| Preface: Fairness and Bias in AI: Insights from AEQUITAS 2023 | Calegari R.; Aler A.; Gabriel T.; Castane G.; Dignum V.; Milano M. | 2023-01-01 | - | Sun SITE Central Europe (CEUR), Technical University of Aachen (RWTH) | 2.02 Prefazione | - |
| Proceedings of the 1st Workshop on Fairness and Bias in AI, AEQUITAS 2023 co-located with 26th European Conference on Artificial Intelligence (ECAI 2023) | Roberta Calegari, Andrea Aler Tubella, Gabriel González Castañe, Virginia Dignum, Michela Milano | 2023-01-01 | - | CEUR-WS | 3.02 Curatela | xpreface.pdf |
| Towards Symbiotic Creativity: A Methodological Approach to Compare Human and AI Robotic Dance Creations | De Filippo, Allegra; Giuliani, Luca; Mancini, Eleonora; Borghesi, Andrea; Mello, Paola; Milano, M...ichela | 2023-01-01 | - | ijcai | 4.01 Contributo in Atti di convegno | 0644.pdf |
| A Multi-modal Perspective for the Artistic Evaluation of Robotic Dance Performances | Luca Giuliani, Allegra De Filippo, Andrea Borghesi, Paola Mello, Michela Milano | 2022-01-01 | - | - | 4.01 Contributo in Atti di convegno | - |
| Anomaly Detection and Anticipation in High Performance Computing Systems | Borghesi A.; Molan M.; Milano M.; Bartolini A. | 2022-01-01 | IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS | - | 1.01 Articolo in rivista | TPDS_SI_Exascale_AnomalyAnticipation_REV.pdf |
| Do You Like Dancing Robots? AI Can Tell You Why | De Filippo A.; Mello P.; Milano M. | 2022-01-01 | - | - | 4.01 Contributo in Atti di convegno | FAIA-351-FAIA220064.pdf |
| HADA: An automated tool for hardware dimensioning of AI applications | De Filippo, A; Borghesi, A; Boscarino, A; Milano, M | 2022-01-01 | KNOWLEDGE-BASED SYSTEMS | - | 1.01 Articolo in rivista | HADA: an Automated Tool for Hardware Dimensioning of AI Applications.pdf |
| Informed Deep Learning for Epidemics Forecasting | Federico Baldo, Michele Iannello, Michele Lombardi, Michela Milano | 2022-01-01 | - | IOS Press BV | 4.01 Contributo in Atti di convegno | FAIA-351-FAIA220067.pdf |
| An Analysis of Regularized Approaches for Constrained Machine Learning | Lombardi, Michele; Baldo, Federico; Borghesi, Andrea; Milano, Michela | 2021-01-01 | - | Springer | 4.01 Contributo in Atti di convegno | tailor2020_paper58_camReady.pdf |
| Injecting Domain Knowledge in Neural Networks: A Controlled Experiment on a Constrained Problem | Silvestri M.; Lombardi M.; Milano M. | 2021-01-01 | - | Springer Science and Business Media Deutschland GmbH | 4.01 Contributo in Atti di convegno | CPAIOR_2021__Knowledge_injection_in_DNNs.pdf |
| Integrated Offline and Online Decision Making under Uncertainty | De Filippo, Allegra; Lombardi, Michele; Milano, Michela | 2021-01-01 | THE JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH | - | 1.01 Articolo in rivista | 12333-Article (PDF)-25701-1-10-20210109.pdf |
| Teaching the Old Dog New Tricks: Supervised Learning with Constraints |
Fabrizio Detassis, Michele Lombardi, Michela Milano |
2021-01-01 | - | {AAAI} Press | 4.01 Contributo in Atti di convegno | AAAI2021___Teaching_the_Old_Dog_new_Tricks.pdf |
| Combining learning and optimization for transprecision computing | Borghesi, Andrea; Tagliavini, Giuseppe; Lombardi, Michele; Benini, Luca; Milano, Michela | 2020-01-01 | - | - | 4.01 Contributo in Atti di convegno | Combining Learning and Optimization for Transprecision.pdf |
| Hybrid offline/online optimization under uncertainty | De Filippo A.; Lombardi M.; Milano M. | 2020-01-01 | - | IOS Press BV | 4.01 Contributo in Atti di convegno | FAIA-325-FAIA200443.pdf |
| Injecting domain knowledge in neural networks: A controlled experiment on a constrained problem | Silvestri M.; Lombardi M.; Milano M. | 2020-01-01 | - | CEUR-WS | 4.01 Contributo in Atti di convegno | silvestri.pdf |
| Injective Domain Knowledge in Neural Networks for Transprecision Computing | Andrea Borghesi, Federico Baldo, Michele Lombardi, Michela Milano | 2020-01-01 | - | Springer | 4.01 Contributo in Atti di convegno | main.pdf |
| Teaching the old dog new tricks: Supervised learning with constraints | Detassis F.; Lombardi M.; Milano M. | 2020-01-01 | - | CEUR-WS | 4.01 Contributo in Atti di convegno | NeHuAI2020___Teaching_the_Old_Dog_new_Tricks.pdf |