| 2025 | IJCNN | (Sometimes) Less is More: Mitigating the Complexity of Rule-based Representation for Interpretable Classification. | Luca Bergamin, Roberto Confalonieri, Fabio Aiolli |
| 2025 | IJCNN | Integrating Background Knowledge in Medical Semantic Segmentation with Logic Tensor Networks. | Luca Bergamin, Giovanna Maria Dimitri, Fabio Aiolli |
| 2024 | ECIR | Mitigating Data Sparsity via Neuro-Symbolic Knowledge Transfer. | Tommaso Carraro, Alessandro Daniele, Fabio Aiolli, Luciano Serafini |
| 2022 | ESANN | Price direction prediction in financial markets, using Random Forest and Adaboost. | Mohammadmahdi Ghahramani, Fabio Aiolli |
| 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 | NeSy | Logic Tensor Networks for Top-N Recommendation. | Tommaso Carraro, Alessandro Daniele, Fabio Aiolli, Luciano Serafini |
| 2021 | ESANN | Privacy-Preserving Kernel Computation For Vertically Partitioned Data. | Mirko Polato, Alberto Gallinaro, Fabio Aiolli |
| 2021 | IJCNN | Exploring the structure of BERT through Kernel Learning. | Ivano Lauriola, Alberto Lavelli, Alessandro Moschitti, Fabio Aiolli |
| 2020 | CogSci | Automatic Detection of Cross-language Verbal Deception. | Pasquale Capuozzo, Ivano Lauriola, Carlo Strapparava, Fabio Aiolli, Giuseppe Sartori |
| 2020 | ESANN | Exploring the feature space of character-level embeddings. | Ivano Lauriola, Stefano Campese, Alberto Lavelli, Fabio Rinaldi, Fabio Aiolli |
| 2020 | ESANN | Language processing in the era of deep learning. | Ivano Lauriola, Alberto Lavelli, Fabio Aiolli |
| 2020 | ESORICS | Big Enough to Care Not Enough to Scare! Crawling to Attack Recommender Systems. | Fabio Aiolli, Mauro Conti, Stjepan Picek, Mirko Polato |
| 2020 | ICANN | Monotone Deep Spectrum Kernels. | Ivano Lauriola, Fabio Aiolli |
| 2020 | LREC | DecOp: A Multilingual and Multi-domain Corpus For Detecting Deception In Typed Text. | Pasquale Capuozzo, Ivano Lauriola, Carlo Strapparava, Fabio Aiolli, Giuseppe Sartori |
| 2019 | AAAI | Efficient Online Learning for Mapping Kernels on Linguistic Structures. | Giovanni Da San Martino, Alessandro Sperduti, Fabio Aiolli, Alessandro Moschitti |
| 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 | ESANN | Fast hyperparameter selection for graph kernels via subsampling and multiple kernel learning. | Michele Donini, Nicol Navarin, Ivano Lauriola, Fabio Aiolli, Fabrizio Costa |
| 2017 | ESANN | Learning dot-product polynomials for multiclass problems. | Ivano Lauriola, Michele Donini, 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 | ESANN | Advances in Learning with Kernels: Theory and Practice in a World of growing Constraints. | Luca Oneto, Nicol Navarin, Michele Donini, Fabio Aiolli, Davide Anguita |
| 2016 | ESANN | Measuring the Expressivity of Graph Kernels through the Rademacher Complexity. | Luca Oneto, Nicol Navarin, Michele Donini, Alessandro Sperduti, Fabio Aiolli, Davide Anguita |
| 2016 | RecSys | A preliminary study on a recommender system for the job recommendation challenge. | Mirko Polato, Fabio Aiolli |
| 2015 | ESANN | Feature and kernel learning. | Vernica Boln-Canedo, Michele Donini, Fabio Aiolli |
| 2014 | ESANN | Easy multiple kernel learning. | Fabio Aiolli, Michele Donini |
| 2014 | ICANN | Learning Anisotropic RBF Kernels. | Fabio Aiolli, Michele Donini |
| 2014 | Mobiquitous | ClimbTheWorld: real-time stairstep counting to increase physical activity. | Fabio Aiolli, Matteo Ciman, Michele Donini, Ombretta Gaggi |
| 2014 | RecSys | Convex AUC optimization for top-N recommendation with implicit feedback. | Fabio Aiolli |
| 2013 | RecSys | Efficient top-n recommendation for very large scale binary rated datasets. | Fabio Aiolli |
| 2011 | BPM | A Business Process Metric Based on the Alpha Algorithm Relations. | Fabio Aiolli, Andrea Burattin, Alessandro Sperduti |
| 2011 | ICANN | Extending Tree Kernels with Topological Information. | Fabio Aiolli, Giovanni Da San Martino, Alessandro Sperduti |
| 2010 | ICANN | A New Tree Kernel Based on SOM-SD. | Fabio Aiolli, Giovanni Da San Martino, Alessandro Sperduti |
| 2009 | CIDM | Application of the preference learning model to a human resources selection task. | Fabio Aiolli, Michele De Filippo De Grazia, Alessandro Sperduti |
| 2009 | ESANN | Supervised learning as preference optimization. | Fabio Aiolli, Alessandro Sperduti |
| 2009 | ICML | Route kernels for trees. | Fabio Aiolli, Giovanni Da San Martino, Alessandro Sperduti |
| 2008 | ICANN | A Kernel Method for the Optimization of the Margin Distribution. | Fabio Aiolli, Giovanni Da San Martino, Alessandro Sperduti |
| 2007 | CIDM | Efficient Kernel-based Learning for Trees. | Fabio Aiolli, Giovanni Da San Martino, Alessandro Sperduti, Alessandro Moschitti |
| 2007 | ESANN | "Kernelized" Self-Organizing Maps for Structured Data. | Fabio Aiolli, Giovanni Da San Martino, Alessandro Sperduti, Markus Hagenbuchner |
| 2007 | IJCNN | Preference Learning for Category-Ranking based Interactive Text Categorization. | Fabio Aiolli, Fabrizio Sebastiani, Alessandro Sperduti |
| 2006 | ICDM | Fast On-line Kernel Learning for Trees. | Fabio Aiolli, Giovanni Da San Martino, Alessandro Sperduti, Alessandro Moschitti |
| 2005 | ICDM | A Preference Model for Structured Supervised Learning Tasks. | Fabio Aiolli |
| 2003 | IJCAI | Multi-prototype Support Vector Machine. | Fabio Aiolli, Alessandro Sperduti |
| 2001 | IJCAI | A Simple Additive Re-weighting Strategy for Improving Margins. | Fabio Aiolli, Alessandro Sperduti |