| 2026 | ESANN | When Curvature Counts: Hyperbolic Geometry in Prototype-Based Image Classification. | Silvia Grosso, Samuele Fonio, Mirko Polato, Roberto Esposito, Sara Bouchenak |
| 2025 | CIKM | A Tutorial on Hypergraph Neural Networks: An In-Depth and Step-By-Step Guide. | Sunwoo Kim, Soo Yong Lee, Yue Gao, Alessia Antelmi, Mirko Polato, Kijung Shin |
| 2025 | ECAI | Fed2RC: Federated Rocket Kernels and Ridge Classifier for Time Series Classification. | Bruno Casella, Samuele Fonio, Lorenzo Sciandra, Claudio Gallicchio, Marco Aldinucci, Mirko Polato, Roberto Esposito |
| 2025 | KDD | Hypergraph Motif Representation Learning. | Alessia Antelmi, Gennaro Cordasco, Daniele De Vinco, Valerio Di Pasquale, Mirko Polato, Carmine Spagnuolo |
| 2024 | ESANN | Vision Language Models as Policy Learners in Reinforcement Learning Environments. | Giovanni Bonetta, Davide Zago, Rossella Cancelliere, Mirko Polato, Bernardo Magnini |
| 2024 | ESANN | FedHP: Federated Learning with Hyperspherical Prototypical Regularization. | Samuele Fonio, Mirko Polato, Roberto Esposito |
| 2024 | ESANN | Machine learning in distributed, federated and non-stationary environments - recent trends. | Mirko Polato, Barbara Hammer, Frank-Michael Schleif |
| 2024 | KDD | A Survey on Hypergraph Neural Networks: An In-Depth and Step-By-Step Guide. | Sunwoo Kim, Soo Yong Lee, Yue Gao, Alessia Antelmi, Mirko Polato, Kijung Shin |
| 2023 | WWW | 1st Workshop on Federated Learning Technologies. | Mirko Polato, Roberto Esposito, Walter Riviera, Zenglin Xu, Irwin King |
| 2022 | ESANN | Bayes Point Rule Set Learning. | Mirko Polato, Fabio Aiolli, Luca Bergamin, Tommaso Carraro |
| 2022 | ICANN | Conditioned Variational Autoencoder for Top-N Item Recommendation. | Tommaso Carraro, Mirko Polato, Luca Bergamin, Fabio Aiolli |
| 2022 | IJCNN | Novel Applications for VAE-based Anomaly Detection Systems. | Luca Bergamin, Tommaso Carraro, Mirko Polato, Fabio Aiolli |
| 2022 | IJCNN | Boosting the Federation: Cross-Silo Federated Learning without Gradient Descent. | Mirko Polato, Roberto Esposito, Marco Aldinucci |
| 2021 | ESANN | Privacy-Preserving Kernel Computation For Vertically Partitioned Data. | Mirko Polato, Alberto Gallinaro, Fabio Aiolli |
| 2021 | IJCNN | Federated Variational Autoencoder for Collaborative Filtering. | Mirko Polato |
| 2020 | ESORICS | Big Enough to Care Not Enough to Scare! Crawling to Attack Recommender Systems. | Fabio Aiolli, Mauro Conti, Stjepan Picek, Mirko Polato |
| 2019 | AAAI | Interpretable Preference Learning: A Game Theoretic Framework for Large Margin On-Line Feature and Rule Learning. | Mirko Polato, Fabio Aiolli |
| 2019 | ICANN | Evaluation of Tag Clusterings for User Profiling in Movie Recommendation. | Guglielmo Faggioli, Mirko Polato, Ivano Lauriola, Fabio Aiolli |
| 2019 | ICANN | Playing the Large Margin Preference Game. | Mirko Polato, Guglielmo Faggioli, Ivano Lauriola, Fabio Aiolli |
| 2019 | SAC | Mind your wallet's privacy: identifying Bitcoin wallet apps and user's actions through network traffic analysis. | Fabio Aiolli, Mauro Conti, Ankit Gangwal, Mirko Polato |
| 2018 | ESANN | The minimum effort maximum output principle applied to Multiple Kernel Learning. | Ivano Lauriola, Mirko Polato, Fabio Aiolli |
| 2018 | ESANN | Boolean kernels for interpretable kernel machines. | Mirko Polato, Fabio Aiolli |
| 2018 | ICANN | Learning Preferences for Large Scale Multi-label Problems. | Ivano Lauriola, Mirko Polato, Alberto Lavelli, Fabio Rinaldi, Fabio Aiolli |
| 2018 | ICANN | A Game-Theoretic Framework for Interpretable Preference and Feature Learning. | Mirko Polato, Fabio Aiolli |
| 2018 | RecSys | Efficient Similarity Based Methods For The Playlist Continuation Task. | Guglielmo Faggioli, Mirko Polato, Fabio Aiolli |
| 2017 | ICANN | Radius-Margin Ratio Optimization for Dot-Product Boolean Kernel Learning. | Ivano Lauriola, Mirko Polato, Fabio Aiolli |
| 2017 | ICANN | Classification of Categorical Data in the Feature Space of Monotone DNFs. | Mirko Polato, Ivano Lauriola, Fabio Aiolli |
| 2016 | ESANN | Kernel based collaborative filtering for very large scale top-N item recommendation. | Fabio Aiolli, Mirko Polato |
| 2016 | RecSys | A preliminary study on a recommender system for the job recommendation challenge. | Mirko Polato, Fabio Aiolli |
| 2014 | IJCNN | Data-aware remaining time prediction of business process instances. | Mirko Polato, Alessandro Sperduti, Andrea Burattin, Massimiliano de Leoni |