Simulation Of Incentive Mechanisms For Renewable Energy Policies. - Andrea Borghesi; Michela Milano; Marco Gavanelli; Tony Woods (ECMS, 2013)

Proactive Workload Dispatching on the EURORA Supercomputer. - Andrea Bartolini; Andrea Borghesi; Thomas Bridi; Michele Lombardi 001; Michela Milano (CP, 2014)

Agent Based Simulation of Incentive Mechanisms on Photovoltaic Adoption. - Valerio Iachini; Andrea Borghesi; Michela Milano (AI*IA, 2015)

Power Capping in High Performance Computing Systems. - Andrea Borghesi; Francesca Collina; Michele Lombardi 001; Michela Milano; Luca Benini (CP, 2015)

MS3: A Mediterranean-stile job scheduler for supercomputers - do less when it's too hot! - Andrea Borghesi; Christian Conficoni; Michele Lombardi 001; Andrea Bartolini (HPCS, 2015)

Predictive Modeling for Job Power Consumption in HPC Systems. - Andrea Borghesi; Andrea Bartolini; Michele Lombardi 001; Michela Milano; Luca Benini (ISC, 2016)

Design of an Energy Aware Petaflops Class High Performance Cluster Based on Power Architecture. - Wissam Abu Ahmad; Andrea Bartolini; Francesco Beneventi; Luca Benini; Andrea Borghesi; Marco Cicala; Privato Forestieri; Cosimo Gianfreda; Daniele Gregori; Antonio Libri; Filippo Spiga; Simone Tinti (IPDPS Workshops, 2017)

Data-Driven Job Dispatching in HPC Systems. - Cristian Galleguillos; Alina Sîrbu; Zeynep Kiziltan; Özalp Babaoglu; Andrea Borghesi; Thomas Bridi (MOD, 2017)

Power-Aware Job Dispatching in High Performance Computing Systems. - Andrea Borghesi (2017)

The D.A.V.I.D.E. big-data-powered fine-grain power and performance monitoring support. - Andrea Bartolini; Andrea Borghesi; Antonio Libri; Francesco Beneventi; Daniele Gregori; Simone Tinti; Cosimo Gianfreda; Piero Altoe (CF, 2018)

FINJ: A Fault Injection Tool for HPC Systems. - Alessio Netti; Zeynep Kiziltan; Özalp Babaoglu; Alina Sîrbu; Andrea Bartolini; Andrea Borghesi (Euro-Par Workshops, 2018)

Energy and Power Aware Job Scheduling and Resource Management: Global Survey - Initial Analysis. - Matthias Maiterth; Gregory A. Koenig; Kevin T. Pedretti; Siddhartha Jana; Natalie J. Bates; Andrea Borghesi; Dave Montoya; Andrea Bartolini; Milos Puzovic (IPDPS Workshops, 2018)

Scheduling-based power capping in high performance computing systems. - Andrea Borghesi; Andrea Bartolini; Michele Lombardi 001; Michela Milano; Luca Benini (Sustain. Comput. Informatics Syst., 2018)

Anomaly Detection Using Autoencoders in High Performance Computing Systems. - Andrea Borghesi; Andrea Bartolini; Michele Lombardi 001; Michela Milano; Luca Benini (AAAI, 2019)

Online Anomaly Detection in HPC Systems. - Andrea Borghesi; Antonio Libri; Luca Benini; Andrea Bartolini (AICAS, 2019)

Frequency Assignment in High Performance Computing Systems. - Andrea Borghesi; Michela Milano; Luca Benini (AI*IA, 2019)

Online Fault Classification in HPC Systems Through Machine Learning. - Alessio Netti; Zeynep Kiziltan; Özalp Babaoglu; Alina Sîrbu; Andrea Bartolini; Andrea Borghesi (Euro-Par, 2019)

Paving the Way Toward Energy-Aware and Automated Datacentre. - Andrea Bartolini; Francesco Beneventi; Andrea Borghesi; Daniele Cesarini; Antonio Libri; Luca Benini; Carlo Cavazzoni (ICPP Workshops, 2019)

A semisupervised autoencoder-based approach for anomaly detection in high performance computing systems. - Andrea Borghesi; Andrea Bartolini; Michele Lombardi 001; Michela Milano; Luca Benini (Eng. Appl. Artif. Intell., 2019)

Pricing schemes for energy-efficient HPC systems: Design and exploration. - Andrea Borghesi; Andrea Bartolini; Michela Milano; Luca Benini (Int. J. High Perform. Comput. Appl., 2019)

Combining learning and optimization for transprecision computing. - Andrea Borghesi; Giuseppe Tagliavini; Michele Lombardi 001; Luca Benini; Michela Milano (CF, 2020)

Injective Domain Knowledge in Neural Networks for Transprecision Computing. - Andrea Borghesi; Federico Baldo; Michele Lombardi 001; Michela Milano (LOD (1), 2020)

An Analysis of Regularized Approaches for Constrained Machine Learning. - Michele Lombardi 001; Federico Baldo; Andrea Borghesi; Michela Milano (TAILOR, 2020)

Improving Deep Learning Models via Constraint-Based Domain Knowledge: a Brief Survey. - Andrea Borghesi; Federico Baldo; Michela Milano (CoRR, 2020)

End-to-end learning for semiquantitative rating of COVID-19 severity on Chest X-rays. - Alberto Signoroni; Mattia Savardi; Sergio Benini; Nicola Adami; Riccardo Leonardi; Paolo Gibellini; Filippo Vaccher; Marco Ravanelli; Andrea Borghesi; Roberto Maroldi; Davide Farina (CoRR, 2020)

A machine learning approach to online fault classification in HPC systems. - Alessio Netti; Zeynep Kiziltan; Özalp Babaoglu; Alina Sîrbu; Andrea Bartolini; Andrea Borghesi (Future Gener. Comput. Syst., 2020)

Countdown Slack: A Run-Time Library to Reduce Energy Footprint in Large-Scale MPI Applications. - Daniele Cesarini; Andrea Bartolini; Andrea Borghesi; Carlo Cavazzoni; Mathieu Luisier; Luca Benini (IEEE Trans. Parallel Distributed Syst., 2020)

IoTwins: Design and Implementation of a Platform for the Management of Digital Twins in Industrial Scenarios. - Andrea Borghesi; Giuseppe Di Modica; Paolo Bellavista; Varun Gowtham; Alexander Willner; Daniel Nehls; Florian Kintzler; Stephan Cejka; Simone Rossi Tisbeni; Alessandro Costantini; Matteo Galletti; Marica Antonacci; et al. (CCGRID, 2021)

An Explainable Model for Fault Detection in HPC Systems. - Martin Molan; Andrea Borghesi; Francesco Beneventi; Massimiliano Guarrasi; Andrea Bartolini (ISC Workshops, 2021)

Deep Learning for Virus-Spreading Forecasting: a Brief Survey. - Federico Baldo; Lorenzo Dall'Olio; Mattia Ceccarelli; Riccardo Scheda; Michele Lombardi 001; Andrea Borghesi; Stefano Diciotti; Michela Milano (CoRR, 2021)

BS-Net: Learning COVID-19 pneumonia severity on a large chest X-ray dataset. - Alberto Signoroni; Mattia Savardi; Sergio Benini; Nicola Adami; Riccardo Leonardi; Paolo Gibellini; Filippo Vaccher; Marco Ravanelli; Andrea Borghesi; Roberto Maroldi; Davide Farina (Medical Image Anal., 2021)

A Multi-modal Perspective for the Artistic Evaluation of Robotic Dance Performances. - Luca Giuliani; Allegra De Filippo; Andrea Borghesi; Paola Mello; Michela Milano (CREAI@AI*IA, 2022)

Semi-supervised anomaly detection on a Tier-0 HPC system. - Martin Molan; Andrea Borghesi; Luca Benini; Andrea Bartolini (CF, 2022)

Constrained Hardware Dimensioning for AI Algorithms. - Allegra De Filippo; Andrea Borghesi (PAIS@ECAI, 2022)

Analysing Supercomputer Nodes Behaviour with the Latent Representation of Deep Learning Models. - Martin Molan; Andrea Borghesi; Luca Benini; Andrea Bartolini (Euro-Par, 2022)

Machine Learning Methodologies to Support HPC Systems Operations: Anomaly Detection. - Martin Molan; Andrea Borghesi; Luca Benini; Andrea Bartolini (Euro-Par Workshops, 2022)

Predictive Maintenance Based on Machine Learning Model. - Bassem Hichri; Anass Driate; Andrea Borghesi; Francesco Giovannini (AIAI (2), 2022)

Machine Learning for Combinatorial Optimisation of Partially-Specified Problems: Regret Minimisation as a Unifying Lens. - Stefano Teso; Laurens Bliek; Andrea Borghesi; Michele Lombardi 001; Neil Yorke-Smith; Tias Guns; Andrea Passerini (CoRR, 2022)

Detection Rate and Variability in Measurement of Mandibular Incisive Canal on Cone-Beam Computed Tomography: A Study of 220 Dentate Hemi-Mandibles from Italy. - Andrea Borghesi; Diego Di Salvo; Pietro Ciolli; Teresa Falcone; Marco Ravanelli; Davide Farina; Nicola Carapella (J. Imaging, 2022)

HADA: An automated tool for hardware dimensioning of AI applications. - Allegra De Filippo; Andrea Borghesi; Andrea Boscarino; Michela Milano (Knowl. Based Syst., 2022)

Anomaly Detection and Anticipation in High Performance Computing Systems. - Andrea Borghesi; Martin Molan; Michela Milano; Andrea Bartolini (IEEE Trans. Parallel Distributed Syst., 2022)

Towards Intelligent Music Production: A Sample-based Approach. - Luca Giuliani; Allegra De Filippo; Andrea Borghesi (CREAI@AI*IA, 2023)

Online Job Failure Prediction in an HPC System. - Francesco Antici; Andrea Borghesi; Zeynep Kiziltan (Euro-Par Workshops, 2023)

TinderAI: Support System for Matching AI Algorithms and Embedded Devices. - Matteo Francobaldi; Allegra De Filippo; Andrea Borghesi; Nikola Pizurica; Igor Jovancevic; Tim Llewellynn; Miguel de Prado (FLAIRS, 2023)

A Federated Learning Approach for Anomaly Detection in High Performance Computing. - Emmen Farooq; Andrea Borghesi (ICTAI, 2023)

MusiComb: a Sample-based Approach to Music Generation Through Constraints. - Luca Giuliani; Francesco Ballerini; Allegra De Filippo; Andrea Borghesi (ICTAI, 2023)

Towards Symbiotic Creativity: A Methodological Approach to Compare Human and AI Robotic Dance Creations. - Allegra De Filippo; Luca Giuliani; Eleonora Mancini; Andrea Borghesi; Paola Mello; Michela Milano (IJCAI, 2023)

Graph Neural Networks for Anomaly Anticipation in HPC Systems. - Martin Molan; Junaid Ahmed Khan; Andrea Borghesi; Andrea Bartolini (ICPE (Companion), 2023)

Model for Quantitative Estimation of Functionality Influence on the Final Value of a Software Product. - Gregor Molan; Gregor Dolinar; Jovan Bojkovski; Radu Prodan; Andrea Borghesi; Martin Molan (IEEE Access, 2023)

Design of an energy aware petaflops class high performance cluster based on power architecture. - W. A. Ahmad; Andrea Bartolini; Francesco Beneventi; Luca Benini; Andrea Borghesi; Marco Cicala; Privato Forestieri; Cosimo Gianfreda; Daniele Gregori; Antonio Libri; Filippo Spiga; Simone Tinti (CoRR, 2023)

M100 dataset: time-aggregated data for anomaly detection. - Andrea Borghesi; Carmine Di Santi; Martin Molan; Mohsen Seyedkazemi Ardebili; Alessio Mauri; Massimiliano Guarrasi; Daniela Galetti; Mirko Cestari; Francesco Barchi; Luca Benini; Francesco Beneventi; Andrea Bartolini (Zenodo, 2023)

M100 dataset 1: from 20-03 to 20-12. - Andrea Borghesi; Carmine Di Santi; Martin Molan; Mohsen Seyedkazemi Ardebili; Alessio Mauri; Massimiliano Guarrasi; Daniela Galetti; Mirko Cestari; Francesco Barchi; Luca Benini; Francesco Beneventi; Andrea Bartolini (Zenodo, 2023)

M100 dataset 2: from 21-01 to 21-06. - Andrea Borghesi; Carmine Di Santi; Martin Molan; Mohsen Seyedkazemi Ardebili; Alessio Mauri; Massimiliano Guarrasi; Daniela Galetti; Mirko Cestari; Francesco Barchi; Luca Benini; Francesco Beneventi; Andrea Bartolini (Zenodo, 2023)

M100 dataset 3: from 21-07 to 21-09. - Andrea Borghesi; Carmine Di Santi; Martin Molan; Mohsen Seyedkazemi Ardebili; Alessio Mauri; Massimiliano Guarrasi; Daniela Galetti; Mirko Cestari; Francesco Barchi; Luca Benini; Francesco Beneventi; Andrea Bartolini (Zenodo, 2023)

M100 dataset 4: from 21-10 to 21-12. - Andrea Borghesi; Carmine Di Santi; Martin Molan; Mohsen Seyedkazemi Ardebili; Alessio Mauri; Massimiliano Guarrasi; Daniela Galetti; Mirko Cestari; Francesco Barchi; Luca Benini; Francesco Beneventi; Andrea Bartolini (Zenodo, 2023)

M100 dataset 5: from 22-01 to 22-02. - Andrea Borghesi; Carmine Di Santi; Martin Molan; Mohsen Seyedkazemi Ardebili; Alessio Mauri; Massimiliano Guarrasi; Daniela Galetti; Mirko Cestari; Francesco Barchi; Luca Benini; Francesco Beneventi; Andrea Bartolini (Zenodo, 2023)

M100 dataset 6: 22-03. - Andrea Borghesi; Carmine Di Santi; Martin Molan; Mohsen Seyedkazemi Ardebili; Alessio Mauri; Massimiliano Guarrasi; Daniela Galetti; Mirko Cestari; Francesco Barchi; Luca Benini; Francesco Beneventi; Andrea Bartolini (Zenodo, 2023)

M100 dataset 7: 22-04. - Andrea Borghesi; Carmine Di Santi; Martin Molan; Mohsen Seyedkazemi Ardebili; Alessio Mauri; Massimiliano Guarrasi; Daniela Galetti; Mirko Cestari; Francesco Barchi; Luca Benini; Francesco Beneventi; Andrea Bartolini (Zenodo, 2023)

M100 dataset 8: 22-05. - Andrea Borghesi; Carmine Di Santi; Martin Molan; Mohsen Seyedkazemi Ardebili; Alessio Mauri; Massimiliano Guarrasi; Daniela Galetti; Mirko Cestari; Francesco Barchi; Luca Benini; Francesco Beneventi; Andrea Bartolini (Zenodo, 2023)

M100 dataset 9: 22-06. - Andrea Borghesi; Carmine Di Santi; Martin Molan; Mohsen Seyedkazemi Ardebili; Alessio Mauri; Massimiliano Guarrasi; Daniela Galetti; Mirko Cestari; Francesco Barchi; Luca Benini; Francesco Beneventi; Andrea Bartolini (Zenodo, 2023)

M100 dataset 10: 22-07. - Andrea Borghesi; Carmine Di Santi; Martin Molan; Mohsen Seyedkazemi Ardebili; Alessio Mauri; Massimiliano Guarrasi; Daniela Galetti; Mirko Cestari; Francesco Barchi; Luca Benini; Francesco Beneventi; Andrea Bartolini (Zenodo, 2023)

M100 dataset 11: 22-08. - Andrea Borghesi; Carmine Di Santi; Martin Molan; Mohsen Seyedkazemi Ardebili; Alessio Mauri; Massimiliano Guarrasi; Daniela Galetti; Mirko Cestari; Francesco Barchi; Luca Benini; Francesco Beneventi; Andrea Bartolini (Zenodo, 2023)

M100 dataset 12: 22-09. - Andrea Borghesi; Carmine Di Santi; Martin Molan; Mohsen Seyedkazemi Ardebili; Alessio Mauri; Massimiliano Guarrasi; Daniela Galetti; Mirko Cestari; Francesco Barchi; Luca Benini; Francesco Beneventi; Andrea Bartolini (Zenodo, 2023)

ExaMon-X: A Predictive Maintenance Framework for Automatic Monitoring in Industrial IoT Systems. - Andrea Borghesi; Alessio Burrello; Andrea Bartolini (IEEE Internet Things J., 2023)

RUAD: Unsupervised anomaly detection in HPC systems. - Martin Molan; Andrea Borghesi; Daniele Cesarini; Luca Benini; Andrea Bartolini (Future Gener. Comput. Syst., 2023)

LSTM-Based Unsupervised Anomaly Detection in High-Performance Computing: A Federated Learning Approach. - Emmen Farooq; Andrea Borghesi (IEEE Big Data, 2024)

Expert-MusiComb: Injective Domain Knowledge in a Neuro-Symbolic Approach for Music Generation. - Lorenzo Tribuiani; Luca Giuliani; Allegra De Filippo; Andrea Borghesi (CREAI@ECAI, 2024)

Unveiling Computer Chess Evolution: Can Machine Learning Detect Historical Trends? - Andrea Borghesi; Paolo Ciancarini; Angelo Di Iorio; Gianluca Moro (ICEC, 2024)

Harnessing federated learning for anomaly detection in supercomputer nodes. - Emmen Farooq; Michela Milano; Andrea Borghesi (Future Gener. Comput. Syst., 2024)

GRAAFE: GRaph Anomaly Anticipation Framework for Exascale HPC systems. - Martin Molan; Mohsen Seyedkazemi Ardebili; Junaid Ahmed Khan; Francesco Beneventi; Daniele Cesarini; Andrea Borghesi; Andrea Bartolini (Future Gener. Comput. Syst., 2024)

Addressing Bias and Data Scarcity in AI-Based Skin Disease Diagnosis with Non-Dermoscopic Images. - Chiara Bellatreccia; Daniele Zama; Arianna Dondi; Luca Pierantoni; Andreozzi Laura; Iria Neri; Marcello Lanari; Andrea Borghesi; Roberta Calegari (AIMMES, 2025)

UoPC: A User-Based Online Framework to Predict Job Power Consumption in HPC Systems. - Francesco Antici; Andrea Borghesi; Jens Domke; Zeynep Kiziltan (ISC, 2025)

Machine learning approaches to predict the execution time of the meteorological simulation software COSMO. - Allegra De Filippo; Emanuele Di Giacomo; Andrea Borghesi (J. Intell. Inf. Syst., 2025)

An online algorithm for power consumption prediction of HPC workload. - Francesco Antici; Andrea Borghesi; Zeynep Kiziltan; Jens Domke; Andrea Bartolini (Future Gener. Comput. Syst., 2026)