| 2026 | AAAI | SOM Directions Are Better than One: Multi-Directional Refusal Suppression in Language Models. | Giorgio Piras, Raffaele Mura, Fabio Brau, Luca Oneto, Fabio Roli, Battista Biggio |
| 2026 | ESANN | Multi-label Complementary Labels Learning under Hard Logical Constraints. | Luca Oneto, Yi Gao, Davide Anguita, Fabio Roli, Min-Ling Zhang, Fulvio Mastrogiovanni |
| 2026 | ESANN | Neuro Symbolic AI and Complex Data. | Luca Oneto, Nicol Navarin, Luca Pasa, Davide Rigoni, Davide Anguita |
| 2026 | ESANN | Ensembling Post-Hoc Image Explanations: When It Works, When It Fails, and How to Tell the Difference. | Luca Oneto, Jinhua Xu, Davide Anguita, Fabio Roli, Jing Yuan |
| 2026 | KR | Optimal In-Station Train Dispatching via Symbolic Pattern Planning. | Matteo Cardellini, Enrico Giunchiglia, Davide Anguita, Carmelo Lofiego, Luca Oneto, Pietro Ratto |
| 2025 | ESANN | Reconciling Grokking with Statistical Learning Theory. | Luca Oneto, Sandro Ridella, Andrea Coraddu, Davide Anguita |
| 2025 | IWANN | Physics Informed Machine Learning for Power Flow Analysis: Injecting Knowledge via Pre-, In-, and Post-processing. | Guido Parodi, Giulio Ferro, Michela Robba, Andrea Coraddu, Francesca Cipollini, Davide Anguita, Luca Oneto |
| 2024 | ESANN | Informed Machine Learning: Excess Risk and Generalization. | Luca Oneto, Davide Anguita, Sandro Ridella |
| 2024 | ESANN | Informed Machine Learning for Complex Data. | Luca Oneto, Nicol Navarin, Alessio Micheli, Luca Pasa, Claudio Gallicchio, Davide Bacciu, Davide Anguita |
| 2024 | ICMLA | Mitigating Unfair Regression in Machine Learning Model Updates. | Irene Buselli, Anna Pallars Lpez, Eduard Martn Jimnez, Davide Anguita, Fabio Roli, Luca Oneto |
| 2024 | ICMLA | Toward Measuring and Understanding the Overvalidation Phenomena. | Fabrizio Mori, Antonio Emanuele Cin, Fabio Roli, Davide Anguita, Luca Oneto |
| 2023 | DSAA | Short-term Forecast and Long-term Simulation for Accurate Energy Consumption Prediction. | Daniele Giampaoli, Francesca Cipollini, Denise Maffione, Luca Oneto |
| 2023 | ESANN | Improving Fairness via Intrinsic Plasticity in Echo State Networks. | Andrea Ceni, Davide Bacciu, Valerio De Caro, Claudio Gallicchio, Luca Oneto |
| 2023 | ESANN | Mitigating Robustness Bias: Theoretical Results and Empirical Evidences. | Danilo Franco, Luca Oneto, Davide Anguita |
| 2023 | ESANN | An Empirical Study of Over-Parameterized Neural Models based on Graph Random Features. | Nicol Navarin, Luca Pasa, Luca Oneto, Alessandro Sperduti |
| 2023 | ESANN | Towards Randomized Algorithms and Models that We Can Trust: a Theoretical Perspective. | Luca Oneto, Sandro Ridella, Davide Anguita |
| 2023 | IWANN | Fair Empirical Risk Minimization Revised. | Danilo Franco, Luca Oneto, Davide Anguita |
| 2022 | ESANN | Biased Edge Dropout in NIFTY for Fair Graph Representation Learning. | Federico Caldart, Luca Pasa, Luca Oneto, Alessandro Sperduti, Nicol Navarin |
| 2022 | ESANN | Simple Non Regressive Informed Machine Learning Model for Predictive Maintenance of Railway Critical Assets. | Luca Oneto, Simone Minisi, Andrea Garrone, Renzo Canepa, Carlo Dambra, Davide Anguita |
| 2022 | ESANN | Do We Really Need a New Theory to Understand the Double-Descent? | Luca Oneto, Sandro Ridella, Davide Anguita |
| 2022 | IJCNN | The Importance of Multiple Temporal Scales in Motion Recognition: when Shallow Model can Support Deep Multi Scale Models. | Vincenzo Stefano D'Amato, Luca Oneto, Antonio Camurri, Davide Anguita |
| 2022 | IJCNN | The Importance of Multiple Temporal Scales in Motion Recognition: from Shallow to Deep Multi Scale Models. | Vincenzo Stefano D'Amato, Luca Oneto, Antonio Camurri, Davide Anguita, Zinat Zarandi, Luciano Fadiga, Alessandro D'Ausilio, Thierry Pozzo |
| 2022 | LPNMR | Deep Learning for the Generation of Heuristics in Answer Set Programming: A Case Study of Graph Coloring. | Carmine Dodaro, Davide Ilardi, Luca Oneto, Francesco Ricca |
| 2022 | RO-MAN | Assessing Emotions in Human-Robot Interaction Based on the Appraisal Theory. | Marco Demutti, Vincenzo Stefano D'Amato, Carmine Recchiuto, Luca Oneto, Antonio Sgorbissa |
| 2021 | ACII | Keep it Simple: Handcrafting Feature and Tuning Random Forests and XGBoost to face the Affective Movement Recognition Challenge 2021. | Vincenzo Stefano D'Amato, Luca Oneto, Antonio Camurri, Davide Anguita |
| 2021 | ESANN | In-Station Train Movements Prediction: from Shallow to Deep Multi Scale Models. | Gianluca Boleto, Luca Oneto, Matteo Cardellini, Marco Maratea, Mauro Vallati, Renzo Canepa, Davide Anguita |
| 2021 | ESANN | Complex Data: Learning Trustworthily, Automatically, and with Guarantees. | Luca Oneto, Nicol Navarin, Battista Biggio, Federico Errica, Alessio Micheli, Franco Scarselli, Monica Bianchini, Alessandro Sperduti |
| 2021 | ESANN | The Benefits of Adversarial Defence in Generalisation. | Luca Oneto, Sandro Ridella, Davide Anguita |
| 2021 | ICCS | An Efficient Hybrid Planning Framework for In-Station Train Dispatching. | Matteo Cardellini, Marco Maratea, Mauro Vallati, Gianluca Boleto, Luca Oneto |
| 2021 | IJCNN | Learn and Visually Explain Deep Fair Models: an Application to Face Recognition. | Danilo Franco, Luca Oneto, Nicol Navarin, Davide Anguita |
| 2021 | IWANN | Accuracy and Intrusiveness in Data-Driven Violin Players Skill Levels Prediction: MOCAP Against MYO Against KINECT. | Vincenzo Stefano D'Amato, Erica Volta, Luca Oneto, Gualtiero Volpe, Antonio Camurri, Davide Anguita |
| 2021 | SoCS | A Planning-based Approach for In-Station Train Dispatching. | Matteo Cardellini, Marco Maratea, Mauro Vallati, Gianluca Boleto, Luca Oneto |
| 2020 | DSAA | Learning Fair and Transferable Representations with Theoretical Guarantees. | Luca Oneto, Michele Donini, Massimiliano Pontil, Andreas Maurer |
| 2020 | ESANN | Learning Deep Fair Graph Neural Networks. | Luca Oneto, Nicol Navarin, Michele Donini |
| 2020 | ESANN | Improving the Union Bound: a Distribution Dependent Approach. | Luca Oneto, Sandro Ridella, Davide Anguita |
| 2020 | IJCNN | Towards Online Discovery of Data-Aware Declarative Process Models from Event Streams. | Nicol Navarin, Matteo Cambiaso, Andrea Burattin, Fabrizio Maria Maggi, Luca Oneto, Alessandro Sperduti |
| 2020 | IJCNN | Deep Learning for Cavitating Marine Propeller Noise Prediction at Design Stage. | Luca Oneto, Francesca Cipollini, Leonardo Miglianti, Giorgio Tani, Stefano Gaggero, Michele Viviani, Andrea Coraddu |
| 2020 | IJCNN | General Fair Empirical Risk Minimization. | Luca Oneto, Michele Donini, Massimiliano Pontil |
| 2019 | AIES | Taking Advantage of Multitask Learning for Fair Classification. | Luca Oneto, Michele Donini, Amon Elders, Massimiliano Pontil |
| 2019 | ESANN | Societal Issues in Machine Learning: When Learning from Data is Not Enough. | Davide Bacciu, Battista Biggio, Paulo Lisboa, Jos D. Martn, Luca Oneto, Alfredo Vellido |
| 2019 | ESANN | Fairness and Accountability of Machine Learning Models in Railway Market: are Applicable Railway Laws Up to Regulate Them? | Charlotte Ducuing, Luca Oneto, Renzo Canepa |
| 2019 | ESANN | PAC-Bayes and Fairness: Risk and Fairness Bounds on Distribution Dependent Fair Priors. | Luca Oneto, Michele Donini, Massimiliano Pontil |
| 2019 | IJCNN | Hybrid Model for Cavitation Noise Spectra Prediction. | Francesca Cipollini, Fabiana Miglianti, Luca Oneto, Giorgio Tani, Michele Viviani |
| 2019 | IJCNN | Ensemble Application of Transfer Learning and Sample Weighting for Stock Market Prediction. | Simone Merello, Andrea Picasso Ratto, Luca Oneto, Erik Cambria |
| 2018 | DSAA | Large-Scale Railway Networks Train Movements: A Dynamic, Interpretable, and Robust Hybrid Data Analytics System. | Alessandro Lulli, Luca Oneto, Renzo Canepa, Simone Petralli, Davide Anguita |
| 2018 | ESANN | Emerging trends in machine learning: beyond conventional methods and data. | Luca Oneto, Nicol Navarin, Michele Donini, Davide Anguita |
| 2018 | ESANN | Local Rademacher Complexity Machine. | Luca Oneto, Sandro Ridella, Davide Anguita |
| 2018 | ICDM | Investigating Timing and Impact of News on the Stock Market. | Simone Merello, Andrea Picasso Ratto, Yukun Ma, Luca Oneto, Erik Cambria |
| 2017 | ESANN | Generalization Performances of Randomized Classifiers and Algorithms built on Data Dependent Distributions. | Luca Oneto, Sandro Ridella, Davide Anguita |
| 2017 | ESANN | Dropout Prediction at University of Genoa: a Privacy Preserving Data Driven Approach. | Luca Oneto, Anna Siri, Gianvittorio Luria, Davide Anguita |
| 2017 | ICANN | ReForeSt: Random Forests in Apache Spark. | Alessandro Lulli, Luca Oneto, Davide Anguita |
| 2017 | ICANN | Marine Safety and Data Analytics: Vessel Crash Stop Maneuvering Performance Prediction. | Luca Oneto, Andrea Coraddu, Paolo Sanetti, Olena Karpenko, Francesca Cipollini, Toine Cleophas, Davide Anguita |
| 2017 | IJCNN | Deep graph node kernels: A convex approach. | Luca Oneto, Nicol Navarin, Alessandro Sperduti, Davide Anguita |
| 2016 | DSAA | Advanced Analytics for Train Delay Prediction Systems by Including Exogenous Weather Data. | Luca Oneto, Emanuele Fumeo, Giorgio Clerico, Renzo Canepa, Federico Papa, Carlo Dambra, Nadia Mazzino, Davide Anguita |
| 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 | ESANN | Tuning the Distribution Dependent Prior in the PAC-Bayes Framework based on Empirical Data. | Luca Oneto, Sandro Ridella, Davide Anguita |
| 2016 | ESANN | Random Forests Model Selection. | Ilenia Orlandi, Luca Oneto, Davide Anguita |
| 2015 | ESANN | Model Selection for Big Data: Algorithmic Stability and Bag of Little Bootstraps on GPUs. | Luca Oneto, Bernardo Pilarz, Alessandro Ghio, Davide Anguita |
| 2015 | ESANN | Advances in learning analytics and educational data mining. | Mehrnoosh Vahdat, Alessandro Ghio, Luca Oneto, Davide Anguita, Mathias Funk, Matthias Rauterberg |
| 2015 | ESANN | Human Algorithmic Stability and Human Rademacher Complexity. | Mehrnoosh Vahdat, Luca Oneto, Alessandro Ghio, Davide Anguita, Mathias Funk, Matthias Rauterberg |
| 2015 | IJCNN | Shrinkage learning to improve SVM with hints. | Luca Oneto, Alessandro Ghio, Sandro Ridella, Davide Anguita |
| 2015 | IJCNN | Support vector machines and strictly positive definite kernel: The regularization hyperparameter is more important than the kernel hyperparameters. | Luca Oneto, Alessandro Ghio, Sandro Ridella, Davide Anguita |
| 2015 | IJCNN | Fast convergence of extended Rademacher Complexity bounds. | Luca Oneto, Alessandro Ghio, Sandro Ridella, Davide Anguita |
| 2014 | ESANN | Learning with few bits on small-scale devices: From regularization to energy efficiency. | Davide Anguita, Alessandro Ghio, Luca Oneto, Sandro Ridella |
| 2014 | ESANN | Byte The Bullet: Learning on Real-World Computing Architectures. | Alessandro Ghio, Luca Oneto |
| 2014 | ICANN | Human Activity Recognition on Smartphones with Awareness of Basic Activities and Postural Transitions. | Jorge Luis Reyes-Ortiz, Luca Oneto, Alessandro Ghio, Albert Sam, Davide Anguita, Xavier Parra |
| 2014 | ICDM | Out-of-Sample Error Estimation: The Blessing of High Dimensionality. | Luca Oneto, Alessandro Ghio, Sandro Ridella, Jorge Luis Reyes-Ortiz, Davide Anguita |
| 2014 | IJCNN | Smartphone battery saving by bit-based hypothesis spaces and local Rademacher Complexities. | Davide Anguita, Alessandro Ghio, Luca Oneto, Sandro Ridella |
| 2013 | ESANN | A Public Domain Dataset for Human Activity Recognition using Smartphones. | Davide Anguita, Alessandro Ghio, Luca Oneto, Xavier Parra, Jorge Luis Reyes-Ortiz |
| 2013 | ESANN | A Learning Machine with a Bit-Based Hypothesis Space. | Davide Anguita, Alessandro Ghio, Luca Oneto, Sandro Ridella |
| 2013 | ICANN | Training Computationally Efficient Smartphone-Based Human Activity Recognition Models. | Davide Anguita, Alessandro Ghio, Luca Oneto, Xavier Parra, Jorge Luis Reyes-Ortiz |
| 2013 | ICANN | A Novel Procedure for Training L1-L2 Support Vector Machine Classifiers. | Davide Anguita, Alessandro Ghio, Luca Oneto, Jorge Luis Reyes-Ortiz, Sandro Ridella |
| 2013 | IJCNN | Some results about the Vapnik-Chervonenkis entropy and the rademacher complexity. | Davide Anguita, Alessandro Ghio, Luca Oneto, Sandro Ridella |
| 2013 | IJCNN | A support vector machine classifier from a bit-constrained, sparse and localized hypothesis space. | Davide Anguita, Alessandro Ghio, Luca Oneto, Sandro Ridella |
| 2012 | ESANN | The 'K' in K-fold Cross Validation. | Davide Anguita, Luca Ghelardoni, Alessandro Ghio, Luca Oneto, Sandro Ridella |
| 2012 | ESANN | Structural Risk Minimization and Rademacher Complexity for Regression. | Davide Anguita, Alessandro Ghio, Luca Oneto, Sandro Ridella |
| 2012 | ICANN | Nested Sequential Minimal Optimization for Support Vector Machines. | Alessandro Ghio, Davide Anguita, Luca Oneto, Sandro Ridella, Carlotta Schatten |
| 2012 | ICANN | Rademacher Complexity and Structural Risk Minimization: An Application to Human Gene Expression Datasets. | Luca Oneto, Davide Anguita, Alessandro Ghio, Sandro Ridella |
| 2011 | ESANN | Maximal Discrepancy vs. Rademacher Complexity for error estimation. | Davide Anguita, Alessandro Ghio, Luca Oneto, Sandro Ridella |
| 2011 | IJCNN | In-sample model selection for Support Vector Machines. | Davide Anguita, Alessandro Ghio, Luca Oneto, Sandro Ridella |
| 2011 | IJCNN | Selecting the hypothesis space for improving the generalization ability of Support Vector Machines. | Davide Anguita, Alessandro Ghio, Luca Oneto, Sandro Ridella |
| 2010 | IJCNN | Model selection for support vector machines: Advantages and disadvantages of the Machine Learning Theory. | Davide Anguita, Alessandro Ghio, Noemi Greco, Luca Oneto, Sandro Ridella |