Model selection for support vector machines: Advantages and disadvantages of the Machine Learning Theory. - Davide Anguita; Alessandro Ghio; Noemi Greco; Luca Oneto; Sandro Ridella (IJCNN, 2010)

Maximal Discrepancy vs. Rademacher Complexity for error estimation. - Davide Anguita; Alessandro Ghio; Luca Oneto; Sandro Ridella (ESANN, 2011)

In-sample model selection for Support Vector Machines. - Davide Anguita; Alessandro Ghio; Luca Oneto; Sandro Ridella (IJCNN, 2011)

Selecting the hypothesis space for improving the generalization ability of Support Vector Machines. - Davide Anguita; Alessandro Ghio; Luca Oneto; Sandro Ridella (IJCNN, 2011)

The Impact of Unlabeled Patterns in Rademacher Complexity Theory for Kernel Classifiers. - Luca Oneto; Davide Anguita; Alessandro Ghio; Sandro Ridella (NIPS, 2011)

The 'K' in K-fold Cross Validation. - Davide Anguita; Luca Ghelardoni; Alessandro Ghio; Luca Oneto; Sandro Ridella (ESANN, 2012)

Structural Risk Minimization and Rademacher Complexity for Regression. - Davide Anguita; Alessandro Ghio; Luca Oneto; Sandro Ridella (ESANN, 2012)

Nested Sequential Minimal Optimization for Support Vector Machines. - Alessandro Ghio; Davide Anguita; Luca Oneto; Sandro Ridella; Carlotta Schatten (ICANN (2), 2012)

Rademacher Complexity and Structural Risk Minimization: An Application to Human Gene Expression Datasets. - Luca Oneto; Davide Anguita; Alessandro Ghio; Sandro Ridella (ICANN (2), 2012)

Human Activity Recognition on Smartphones Using a Multiclass Hardware-Friendly Support Vector Machine. - Davide Anguita; Alessandro Ghio; Luca Oneto; Xavier Parra; Jorge Luis Reyes-Ortiz (IWAAL, 2012)

In-sample Model Selection for Trimmed Hinge Loss Support Vector Machine. - Davide Anguita; Alessandro Ghio; Luca Oneto; Sandro Ridella (Neural Process. Lett., 2012)

In-Sample and Out-of-Sample Model Selection and Error Estimation for Support Vector Machines. - Davide Anguita; Alessandro Ghio; Luca Oneto; Sandro Ridella (IEEE Trans. Neural Networks Learn. Syst., 2012)

Human Activity Recognition Using Smartphones. - Jorge Luis Reyes-Ortiz; Davide Anguita; Alessandro Ghio; Luca Oneto; Xavier Parra (UCI Machine Learning Repository, 2012)

A Public Domain Dataset for Human Activity Recognition using Smartphones. - Davide Anguita; Alessandro Ghio; Luca Oneto; Xavier Parra; Jorge Luis Reyes-Ortiz (ESANN, 2013)

A Learning Machine with a Bit-Based Hypothesis Space. - Davide Anguita; Alessandro Ghio; Luca Oneto; Sandro Ridella (ESANN, 2013)

Training Computationally Efficient Smartphone-Based Human Activity Recognition Models. - Davide Anguita; Alessandro Ghio; Luca Oneto; Xavier Parra; Jorge Luis Reyes-Ortiz (ICANN, 2013)

A Novel Procedure for Training L1-L2 Support Vector Machine Classifiers. - Davide Anguita; Alessandro Ghio; Luca Oneto; Jorge Luis Reyes-Ortiz; Sandro Ridella (ICANN, 2013)

Some results about the Vapnik-Chervonenkis entropy and the rademacher complexity. - Davide Anguita; Alessandro Ghio; Luca Oneto; Sandro Ridella (IJCNN, 2013)

A support vector machine classifier from a bit-constrained, sparse and localized hypothesis space. - Davide Anguita; Alessandro Ghio; Luca Oneto; Sandro Ridella (IJCNN, 2013)

Energy Efficient Smartphone-Based Activity Recognition using Fixed-Point Arithmetic. - Davide Anguita; Alessandro Ghio; Luca Oneto; Xavier Parra; Jorge Luis Reyes-Ortiz (J. Univers. Comput. Sci., 2013)

An improved analysis of the Rademacher data-dependent bound using its self bounding property. - Luca Oneto; Alessandro Ghio; Davide Anguita; Sandro Ridella (Neural Networks, 2013)

A Learning Analytics Methodology to Profile Students Behavior and Explore Interactions with a Digital Electronics Simulator. - Mehrnoosh Vahdat; Luca Oneto; Alessandro Ghio; Giuliano Donzellini; Davide Anguita; Mathias Funk; Matthias Rauterberg (EC-TEL, 2014)

Learning with few bits on small-scale devices: From regularization to energy efficiency. - Davide Anguita; Alessandro Ghio; Luca Oneto; Sandro Ridella (ESANN, 2014)

Byte The Bullet: Learning on Real-World Computing Architectures. - Alessandro Ghio; Luca Oneto (ESANN, 2014)

Human Activity Recognition on Smartphones with Awareness of Basic Activities and Postural Transitions. - Jorge Luis Reyes-Ortiz; Luca Oneto; Alessandro Ghio; Albert Samà; Davide Anguita; Xavier Parra (ICANN, 2014)

Out-of-Sample Error Estimation: The Blessing of High Dimensionality. - Luca Oneto; Alessandro Ghio; Sandro Ridella; Jorge Luis Reyes-Ortiz; Davide Anguita (ICDM Workshops, 2014)

Smartphone battery saving by bit-based hypothesis spaces and local Rademacher Complexities. - Davide Anguita; Alessandro Ghio; Luca Oneto; Sandro Ridella (IJCNN, 2014)

Unlabeled patterns to tighten Rademacher complexity error bounds for kernel classifiers. - Davide Anguita; Alessandro Ghio; Luca Oneto; Sandro Ridella (Pattern Recognit. Lett., 2014)

A Deep Connection Between the Vapnik-Chervonenkis Entropy and the Rademacher Complexity. - Davide Anguita; Alessandro Ghio; Luca Oneto; Sandro Ridella (IEEE Trans. Neural Networks Learn. Syst., 2014)

Condition Based Maintenance of Naval Propulsion Plants. - Andrea Coraddu; Luca Oneto; Alessandro Ghio; Stefano Savio; Davide Anguita; Massimo Figari (UCI Machine Learning Repository, 2014)

Performance assessment and uncertainty quantification of predictive models for smart manufacturing systems. - Luca Oneto; Ilenia Orlandi; Davide Anguita (IEEE BigData, 2015)

A Learning Analytics Approach to Correlate the Academic Achievements of Students with Interaction Data from an Educational Simulator. - Mehrnoosh Vahdat; Luca Oneto; Davide Anguita; Mathias Funk; Matthias Rauterberg (EC-TEL, 2015)

Model Selection for Big Data: Algorithmic Stability and Bag of Little Bootstraps on GPUs. - Luca Oneto; Bernardo Pilarz; Alessandro Ghio; Davide Anguita (ESANN, 2015)

Advances in learning analytics and educational data mining. - Mehrnoosh Vahdat; Alessandro Ghio; Luca Oneto; Davide Anguita; Mathias Funk; Matthias Rauterberg (ESANN, 2015)

Human Algorithmic Stability and Human Rademacher Complexity. - Mehrnoosh Vahdat; Luca Oneto; Alessandro Ghio; Davide Anguita; Mathias Funk; Matthias Rauterberg (ESANN, 2015)

Shrinkage learning to improve SVM with hints. - Luca Oneto; Alessandro Ghio; Sandro Ridella; Davide Anguita (IJCNN, 2015)

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 (IJCNN, 2015)

Fast convergence of extended Rademacher Complexity bounds. - Luca Oneto; Alessandro Ghio; Sandro Ridella; Davide Anguita (IJCNN, 2015)

Condition Based Maintenance in Railway Transportation Systems Based on Big Data Streaming Analysis. - Emanuele Fumeo; Luca Oneto; Davide Anguita (INNS Conference on Big Data, 2015)

Big Data Analytics in the Cloud: Spark on Hadoop vs MPI/OpenMP on Beowulf. - Jorge Luis Reyes-Ortiz; Luca Oneto; Davide Anguita (INNS Conference on Big Data, 2015)

Learning Resource-Aware Classifiers for Mobile Devices: From Regularization to Energy Efficiency. - Luca Oneto; Alessandro Ghio; Sandro Ridella; Davide Anguita (Neurocomputing, 2015)

Local Rademacher Complexity: Sharper risk bounds with and without unlabeled samples. - Luca Oneto; Alessandro Ghio; Sandro Ridella; Davide Anguita (Neural Networks, 2015)

Fully Empirical and Data-Dependent Stability-Based Bounds. - Luca Oneto; Alessandro Ghio; Sandro Ridella; Davide Anguita (IEEE Trans. Cybern., 2015)

Smartphone-Based Recognition of Human Activities and Postural Transitions. - Jorge Luis Reyes-Ortiz; Davide Anguita; Luca Oneto; Xavier Parra (UCI Machine Learning Repository, 2015)

Educational Process Mining (EPM): A Learning Analytics Data Set. - Mehrnoosh Vahdat; Luca Oneto; Davide Anguita; Mathias Funk; Matthias Rauterberg (UCI Machine Learning Repository, 2015)

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 (DSAA, 2016)

Advances in Learning with Kernels: Theory and Practice in a World of growing Constraints. - Luca Oneto; Nicolò Navarin; Michele Donini; Fabio Aiolli; Davide Anguita (ESANN, 2016)

Measuring the Expressivity of Graph Kernels through the Rademacher Complexity. - Luca Oneto; Nicolò Navarin; Michele Donini; Alessandro Sperduti; Fabio Aiolli; Davide Anguita (ESANN, 2016)

Tuning the Distribution Dependent Prior in the PAC-Bayes Framework based on Empirical Data. - Luca Oneto; Sandro Ridella; Davide Anguita (ESANN, 2016)

Random Forests Model Selection. - Ilenia Orlandi; Luca Oneto; Davide Anguita (ESANN, 2016)

Delay Prediction System for Large-Scale Railway Networks Based on Big Data Analytics. - Luca Oneto; Emanuele Fumeo; Giorgio Clerico; Renzo Canepa; Federico Papa; Carlo Dambra; Nadia Mazzino; Davide Anguita (INNS Conference on Big Data, 2016)

Vessel monitoring and design in industry 4.0: A data driven perspective. - Luca Oneto; Davide Anguita; Andrea Coraddu; Toine Cleophas; Katerina Xepapa (RTSI, 2016)

Statistical Learning Theory and ELM for Big Social Data Analysis. - Luca Oneto; Federica Bisio; Erik Cambria; Davide Anguita (IEEE Comput. Intell. Mag., 2016)

Transition-Aware Human Activity Recognition Using Smartphones. - Jorge Luis Reyes-Ortiz; Luca Oneto; Albert Samà; Xavier Parra; Davide Anguita (Neurocomputing, 2016)

Can machine learning explain human learning? - Mehrnoosh Vahdat; Luca Oneto; Davide Anguita; Mathias Funk; Matthias Rauterberg (Neurocomputing, 2016)

Tikhonov, Ivanov and Morozov regularization for support vector machine learning. - Luca Oneto; Sandro Ridella; Davide Anguita (Mach. Learn., 2016)

A local Vapnik-Chervonenkis complexity. - Luca Oneto; Davide Anguita; Sandro Ridella (Neural Networks, 2016)

Global Rademacher Complexity Bounds: From Slow to Fast Convergence Rates. - Luca Oneto; Alessandro Ghio; Sandro Ridella; Davide Anguita (Neural Process. Lett., 2016)

PAC-bayesian analysis of distribution dependent priors: Tighter risk bounds and stability analysis. - Luca Oneto; Davide Anguita; Sandro Ridella (Pattern Recognit. Lett., 2016)

Learning Hardware-Friendly Classifiers Through Algorithmic Stability. - Luca Oneto; Sandro Ridella; Davide Anguita (ACM Trans. Embed. Comput. Syst., 2016)

Learning Hardware Friendly Classifiers Through Algorithmic Risk Minimization. - Luca Oneto; Davide Anguita (Advances in Neural Networks, 2016)

Crack random forest for arbitrary large datasets. - Alessandro Lulli; Luca Oneto; Davide Anguita (IEEE BigData, 2017)

Generalization Performances of Randomized Classifiers and Algorithms built on Data Dependent Distributions. - Luca Oneto; Sandro Ridella; Davide Anguita (ESANN, 2017)

Dropout Prediction at University of Genoa: a Privacy Preserving Data Driven Approach. - Luca Oneto; Anna Siri; Gianvittorio Luria; Davide Anguita (ESANN, 2017)

ReForeSt: Random Forests in Apache Spark. - Alessandro Lulli; Luca Oneto; Davide Anguita (ICANN (2), 2017)

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 (ICANN (2), 2017)

Deep graph node kernels: A convex approach. - Luca Oneto; Nicolò Navarin; Alessandro Sperduti; Davide Anguita (IJCNN, 2017)

Semi-supervised Learning for Affective Common-Sense Reasoning. - Luca Oneto; Federica Bisio; Erik Cambria; Davide Anguita (Cogn. Comput., 2017)

SLT-Based ELM for Big Social Data Analysis. - Luca Oneto; Federica Bisio; Erik Cambria; Davide Anguita (Cogn. Comput., 2017)

Measuring the expressivity of graph kernels through Statistical Learning Theory. - Luca Oneto; Nicolò Navarin; Michele Donini; Alessandro Sperduti; Fabio Aiolli; Davide Anguita (Neurocomputing, 2017)

Differential privacy and generalization: Sharper bounds with applications. - Luca Oneto; Sandro Ridella; Davide Anguita (Pattern Recognit. Lett., 2017)

Dynamic Delay Predictions for Large-Scale Railway Networks: Deep and Shallow Extreme Learning Machines Tuned via Thresholdout. - Luca Oneto; Emanuele Fumeo; Giorgio Clerico; Renzo Canepa; Federico Papa; Carlo Dambra; Nadia Mazzino; Davide Anguita (IEEE Trans. Syst. Man Cybern. Syst., 2017)

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 (DSAA, 2018)

Emerging trends in machine learning: beyond conventional methods and data. - Luca Oneto; Nicolò Navarin; Michele Donini; Davide Anguita (ESANN, 2018)

Investigating Timing and Impact of News on the Stock Market. - Simone Merello; Andrea Picasso Ratto; Yukun Ma; Luca Oneto; Erik Cambria (ICDM Workshops, 2018)

Unintrusive Monitoring of Induction Motors Bearings via Deep Learning on Stator Currents. - Francesca Cipollini; Luca Oneto; Andrea Coraddu; Stefano Savio; Davide Anguita (INNS Conference on Big Data, 2018)

Empirical Risk Minimization Under Fairness Constraints. - Michele Donini; Luca Oneto; Shai Ben-David; John Shawe-Taylor; Massimiliano Pontil (NeurIPS, 2018)

Ensemble of Technical Analysis and Machine Learning for Market Trend Prediction. - Andrea Picasso Ratto; Simone Merello; Luca Oneto; Yukun Ma; Lorenzo Malandri; Erik Cambria (SSCI, 2018)

Train Delay Prediction Systems: A Big Data Analytics Perspective. - Luca Oneto; Emanuele Fumeo; Giorgio Clerico; Renzo Canepa; Federico Papa; Carlo Dambra; Nadia Mazzino; Davide Anguita (Big Data Res., 2018)

Advances in artificial neural networks, machine learning and computational intelligence. - Fabio Aiolli; Michael Biehl; Luca Oneto (Neurocomputing, 2018)

Randomized learning: Generalization performance of old and new theoretically grounded algorithms. - Luca Oneto; Francesca Cipollini; Sandro Ridella; Davide Anguita (Neurocomputing, 2018)

Multilayer Graph Node Kernels: Stacking While Maintaining Convexity. - Luca Oneto; Nicolò Navarin; Alessandro Sperduti; Davide Anguita (Neural Process. Lett., 2018)

Condition-based maintenance of naval propulsion systems: Data analysis with minimal feedback. - Francesca Cipollini; Luca Oneto; Andrea Coraddu; Alan John Murphy; Davide Anguita (Reliab. Eng. Syst. Saf., 2018)

Data-Driven Photovoltaic Power Production Nowcasting and Forecasting for Polygeneration Microgrids. - Luca Oneto; Federica Laureri; Michela Robba; Federico Delfino; Davide Anguita (IEEE Syst. J., 2018)

Learning With Kernels: A Local Rademacher Complexity-Based Analysis With Application to Graph Kernels. - Luca Oneto; Nicolò Navarin; Michele Donini; Sandro Ridella; Alessandro Sperduti; Fabio Aiolli; Davide Anguita (IEEE Trans. Neural Networks Learn. Syst., 2018)

Model selection and error estimation without the agonizing pain. - Luca Oneto (WIREs Data Mining Knowl. Discov., 2018)

Taking Advantage of Multitask Learning for Fair Classification. - Luca Oneto; Michele Donini; Amon Elders; Massimiliano Pontil (AIES, 2019)

Societal Issues in Machine Learning: When Learning from Data is Not Enough. - Davide Bacciu; Battista Biggio; Paulo Lisboa; José D. Martín; Luca Oneto; Alfredo Vellido (ESANN, 2019)

Fairness and Accountability of Machine Learning Models in Railway Market: are Applicable Railway Laws Up to Regulate Them? - Charlotte Ducuing; Luca Oneto; Renzo Canepa (ESANN, 2019)

PAC-Bayes and Fairness: Risk and Fairness Bounds on Distribution Dependent Fair Priors. - Luca Oneto; Michele Donini; Massimiliano Pontil (ESANN, 2019)

Hybrid Model for Cavitation Noise Spectra Prediction. - Francesca Cipollini; Fabiana Miglianti; Luca Oneto; Giorgio Tani; Michele Viviani (IJCNN, 2019)

Ensemble Application of Transfer Learning and Sample Weighting for Stock Market Prediction. - Simone Merello; Andrea Picasso Ratto; Luca Oneto; Erik Cambria (IJCNN, 2019)

Cavitation Noise Spectra Prediction with Hybrid Models. - Francesca Cipollini; Fabiana Miglianti; Luca Oneto; Giorgio Tani; Michele Viviani; Davide Anguita (INNSBDDL, 2019)

Predicting Future Market Trends: Which Is the Optimal Window? - Simone Merello; Andrea Picasso Ratto; Luca Oneto; Erik Cambria (INNSBDDL, 2019)

Train Overtaking Prediction in Railway Networks: A Big Data Perspective. - Luca Oneto; Irene Buselli; Alessandro Lulli; Renzo Canepa; Simone Petralli; Davide Anguita (INNSBDDL, 2019)

Restoration Time Prediction in Large Scale Railway Networks: Big Data and Interpretability. - Luca Oneto; Irene Buselli; Paolo Sanetti; Renzo Canepa; Simone Petralli; Davide Anguita (INNSBDDL, 2019)

Fairness in Machine Learning. - Luca Oneto; Silvia Chiappa (INNSBDDL (Tutorials), 2019)

Introduction. - Luca Oneto; Nicolò Navarin; Alessandro Sperduti; Davide Anguita (INNSBDDL (Tutorials), 2019)

Innovation Capability of Firms: A Big Data Approach with Patents. - Linda Ponta; Gloria Puliga; Luca Oneto; Raffaella Manzini (INNSBDDL, 2019)

Visual Analytics for Supporting Conflict Resolution in Large Railway Networks. - Udo Schlegel; Wolfgang Jentner; Juri Buchmüller; Eren Cakmak; Giuliano Castiglia; Renzo Canepa; Simone Petralli; Luca Oneto; Daniel A. Keim; Davide Anguita (INNSBDDL, 2019)

Improving Railway Maintenance Actions with Big Data and Distributed Ledger Technologies. - Roberto Spigolon; Luca Oneto; Dimitar Anastasovski; Nadia Fabrizio; Marie Swiatek; Renzo Canepa; Davide Anguita (INNSBDDL, 2019)

Prescriptive Maintenance of Railway Infrastructure: From Data Analytics to Decision Support. - Alice Consilvio; Paolo Sanetti; Davide Anguita; Carlo Crovetto; Carlo Dambra; Luca Oneto; Federico Papa; Nicola Sacco (MT-ITS, 2019)

Leveraging Labeled and Unlabeled Data for Consistent Fair Binary Classification. - Evgenii Chzhen; Christophe Denis; Mohamed Hebiri; Luca Oneto; Massimiliano Pontil (NeurIPS, 2019)

Mining Big Data with Random Forests. - Alessandro Lulli; Luca Oneto; Davide Anguita (Cogn. Comput., 2019)

Learning Fair and Transferable Representations. - Luca Oneto; Michele Donini; Andreas Maurer; Massimiliano Pontil (CoRR, 2019)

Technical analysis and sentiment embeddings for market trend prediction. - Andrea Picasso Ratto; Simone Merello; Yukun Ma; Luca Oneto; Erik Cambria (Expert Syst. Appl., 2019)

Simple continuous optimal regions of the space of data. - Alessio Carrega; Francesca Cipollini; Luca Oneto (Neurocomputing, 2019)

Advances in artificial neural networks, machine learning and computational intelligence: Selected papers from the 26th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2018). - Luca Oneto; Kerstin Bunte; Frank-Michael Schleif (Neurocomputing, 2019)

Local Rademacher Complexity Machine. - Luca Oneto; Sandro Ridella; Davide Anguita (Neurocomputing, 2019)

Learning Fair and Transferable Representations with Theoretical Guarantees. - Luca Oneto; Michele Donini; Massimiliano Pontil; Andreas Maurer (DSAA, 2020)

Learning Deep Fair Graph Neural Networks. - Luca Oneto; Nicolò Navarin; Michele Donini (ESANN, 2020)

Improving the Union Bound: a Distribution Dependent Approach. - Luca Oneto; Sandro Ridella; Davide Anguita (ESANN, 2020)

Towards Online Discovery of Data-Aware Declarative Process Models from Event Streams. - Nicolò Navarin; Matteo Cambiaso; Andrea Burattin; Fabrizio Maria Maggi; Luca Oneto; Alessandro Sperduti (IJCNN, 2020)

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 (IJCNN, 2020)

General Fair Empirical Risk Minimization. - Luca Oneto; Michele Donini; Massimiliano Pontil (IJCNN, 2020)

Fair regression with Wasserstein barycenters. - Evgenii Chzhen; Christophe Denis; Mohamed Hebiri; Luca Oneto; Massimiliano Pontil (NeurIPS, 2020)

Fair regression via plug-in estimator and recalibration with statistical guarantees. - Evgenii Chzhen; Christophe Denis; Mohamed Hebiri; Luca Oneto; Massimiliano Pontil (NeurIPS, 2020)

Exploiting MMD and Sinkhorn Divergences for Fair and Transferable Representation Learning. - Luca Oneto; Michele Donini; Giulia Luise; Carlo Ciliberto; Andreas Maurer; Massimiliano Pontil (NeurIPS, 2020)

Understanding Violin Players' Skill Level Based on Motion Capture: a Data-Driven Perspective. - Vincenzo Stefano D'Amato; Erica Volta; Luca Oneto; Gualtiero Volpe; Antonio Camurri; Davide Anguita (Cogn. Comput., 2020)

Learning fair models and representations. - Luca Oneto (Intelligenza Artificiale, 2020)

A dynamic, interpretable, and robust hybrid data analytics system for train movements in large-scale railway networks. - Luca Oneto; Irene Buselli; Alessandro Lulli; Renzo Canepa; Simone Petralli; Davide Anguita (Int. J. Data Sci. Anal., 2020)

Advances in artificial neural networks, machine learning and computational intelligence. - Luca Oneto; Kerstin Bunte; Alessandro Sperduti (Neurocomputing, 2020)

Randomized learning and generalization of fair and private classifiers: From PAC-Bayes to stability and differential privacy. - Luca Oneto; Michele Donini; Massimiliano Pontil; John Shawe-Taylor (Neurocomputing, 2020)

Low-Resource Footprint, Data-Driven Malware Detection on Android. - Simone Aonzo; Alessio Merlo; Mauro Migliardi; Luca Oneto; Francesco Palmieri 002 (IEEE Trans. Sustain. Comput., 2020)

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 (ACII (Workshops and Demos), 2021)

In-Station Train Dispatching: A PDDL+ Planning Approach. - Matteo Cardellini; Marco Maratea; Mauro Vallati; Gianluca Boleto; Luca Oneto (ICAPS, 2021)

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 (ESANN, 2021)

Complex Data: Learning Trustworthily, Automatically, and with Guarantees. - Luca Oneto; Nicolò Navarin; Battista Biggio; Federico Errica; Alessio Micheli; Franco Scarselli; Monica Bianchini; Alessandro Sperduti (ESANN, 2021)

The Benefits of Adversarial Defence in Generalisation. - Luca Oneto; Sandro Ridella; Davide Anguita (ESANN, 2021)

An Efficient Hybrid Planning Framework for In-Station Train Dispatching. - Matteo Cardellini; Marco Maratea; Mauro Vallati; Gianluca Boleto; Luca Oneto (ICCS (1), 2021)

Learn and Visually Explain Deep Fair Models: an Application to Face Recognition. - Danilo Franco; Luca Oneto; Nicolò Navarin; Davide Anguita (IJCNN, 2021)

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 (IWANN (2), 2021)

A Planning-based Approach for In-Station Train Dispatching. - Matteo Cardellini; Marco Maratea; Mauro Vallati; Gianluca Boleto; Luca Oneto (SOCS, 2021)

A Machine Learning Analysis of Health Records of Patients With Chronic Kidney Disease at Risk of Cardiovascular Disease. - Davide Chicco; Christopher A. Lovejoy; Luca Oneto (IEEE Access, 2021)

Data analytics and clinical feature ranking of medical records of patients with sepsis. - Davide Chicco; Luca Oneto (BioData Min., 2021)

Marine dual fuel engines monitoring in the wild through weakly supervised data analytics. - Andrea Coraddu; Luca Oneto; Davide Ilardi; Sokratis Stoumpos; Gerasimos Theotokatos (Eng. Appl. Artif. Intell., 2021)

Toward Learning Trustworthily from Data Combining Privacy, Fairness, and Explainability: An Application to Face Recognition. - Danilo Franco; Luca Oneto; Nicolò Navarin; Davide Anguita (Entropy, 2021)

Distribution-Dependent Weighted Union Bound. - Luca Oneto; Sandro Ridella (Entropy, 2021)

Computational intelligence identifies alkaline phosphatase (ALP), alpha-fetoprotein (AFP), and hemoglobin levels as most predictive survival factors for hepatocellular carcinoma. - Davide Chicco; Luca Oneto (Health Informatics J., 2021)

An Enhanced Random Forests Approach to Predict Heart Failure From Small Imbalanced Gene Expression Data. - Davide Chicco; Luca Oneto (IEEE ACM Trans. Comput. Biol. Bioinform., 2021)

A Cloud Architecture for Emotion Recognition Based on the Appraisal Theory (short paper). - Marco Demutti; Vincenzo Stefano D'Amato; Carmine Tommaso Recchiuto; Luca Oneto; Antonio Sgorbissa (AIRO@AI*IA, 2022)

Culture Awareness in Intelligent Systems (short paper). - Ariel Gjaci; Luca Oneto; Carmine Tommaso Recchiuto; Antonio Sgorbissa (AIRO@AI*IA, 2022)

Biased Edge Dropout in NIFTY for Fair Graph Representation Learning. - Federico Caldart; Luca Pasa; Luca Oneto; Alessandro Sperduti; Nicolò Navarin (ESANN, 2022)

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 (ESANN, 2022)

Do We Really Need a New Theory to Understand the Double-Descent? - Luca Oneto; Sandro Ridella; Davide Anguita (ESANN, 2022)

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 (IJCNN, 2022)

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 (IJCNN, 2022)

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 (LPNMR, 2022)

Assessing Emotions in Human-Robot Interaction Based on the Appraisal Theory. - Marco Demutti; Vincenzo Stefano D'Amato; Carmine Recchiuto; Luca Oneto; Antonio Sgorbissa (RO-MAN, 2022)

Data-Driven Methods for Aviation Safety: From Data to Knowledge. - Irene Buselli; Luca Oneto; Carlo Dambra; Christian Verdonk Gallego; Miguel Garcia Martinez (SYSINT, 2022)

Simple Non Regressive Informed Machine Learning Model for Prescriptive Maintenance of Track Circuits in a Subway Environment. - Andrea Garrone; Simone Minisi; Luca Oneto; Carlo Dambra; Marco Borinato; Paolo Sanetti; Giulia Vignola; Federico Papa; Nadia Mazzino; Davide Anguita (SYSINT, 2022)

Deep fair models for complex data: Graphs labeling and explainable face recognition. - Danilo Franco; Nicolò Navarin; Michele Donini; Davide Anguita; Luca Oneto (Neurocomputing, 2022)

Advances in artificial neural networks, machine learning and computational intelligence. - Luca Oneto; Kerstin Bunte; Nicolò Navarin (Neurocomputing, 2022)

Towards learning trustworthily, automatically, and with guarantees on graphs: An overview. - Luca Oneto; Nicolò Navarin; Battista Biggio; Federico Errica; Alessio Micheli; Franco Scarselli; Monica Bianchini; Luca Demetrio; Pietro Bongini; Armando Tacchella; Alessandro Sperduti (Neurocomputing, 2022)

Advances in artificial neural networks, machine learning and computational intelligence. - Luca Oneto; Nicolò Navarin; Frank-Michael Schleif (Neurocomputing, 2022)

The benefits of adversarial defense in generalization. - Luca Oneto; Sandro Ridella; Davide Anguita (Neurocomputing, 2022)

Optimizing Fuel Consumption in Thrust Allocation for Marine Dynamic Positioning Systems. - Miltiadis Kalikatzarakis; Andrea Coraddu; Luca Oneto; Davide Anguita (IEEE Trans Autom. Sci. Eng., 2022)

Identifying the Determinants of Innovation Capability With Machine Learning and Patents. - Linda Ponta; Gloria Puliga; Luca Oneto; Raffaella Manzini (IEEE Trans. Engineering Management, 2022)

Eleven quick tips for data cleaning and feature engineering. - Davide Chicco; Luca Oneto; Erica Tavazzi (PLoS Comput. Biol., 2022)

Introduzione al Progetto di Sistemi Digitali, 2a Edition - Giuliano Donzellini; Luca Oneto; Domenico Ponta; Davide Anguita (Springer, 2023)

Short-term Forecast and Long-term Simulation for Accurate Energy Consumption Prediction. - Daniele Giampaoli; Francesca Cipollini; Denise Maffione; Luca Oneto (DSAA, 2023)

Improving Fairness via Intrinsic Plasticity in Echo State Networks. - Andrea Ceni; Davide Bacciu; Valerio De Caro; Claudio Gallicchio; Luca Oneto (ESANN, 2023)

Mitigating Robustness Bias: Theoretical Results and Empirical Evidences. - Danilo Franco; Luca Oneto; Davide Anguita (ESANN, 2023)

An Empirical Study of Over-Parameterized Neural Models based on Graph Random Features. - Nicolò Navarin; Luca Pasa; Luca Oneto; Alessandro Sperduti (ESANN, 2023)

Towards Randomized Algorithms and Models that We Can Trust: a Theoretical Perspective. - Luca Oneto; Sandro Ridella; Davide Anguita (ESANN, 2023)

Fair Empirical Risk Minimization Revised. - Danilo Franco; Luca Oneto; Davide Anguita (IWANN (1), 2023)

PhishVision: A Deep Learning Based Visual Brand Impersonation Detector for Identifying Phishing Attacks. - Giovanni Graziano; Daniele Ucci; Federica Bisio; Luca Oneto (OL2A (1), 2023)

Physics Informed Data Driven Techniques for Power Flow Analysis. - Guido Parodi; Luca Oneto; Giulio Ferro; Stefano Zampini; Michela Robba; Davide Anguita; Andrea Coraddu (SSCI, 2023)

Human Movement Datasets: An Interdisciplinary Scoping Review. - Temitayo A. Olugbade; Marta Bienkiewicz; Giulia Barbareschi; Vincenzo Stefano D'Amato; Luca Oneto; Antonio Camurri; Catherine Holloway; Mårten Björkman; Peter E. Keller; Martin Clayton; Amanda C. de C. Williams; Nicolas Gold; et al. (ACM Comput. Surv., 2023)

Physically plausible propeller noise prediction via recursive corrections leveraging prior knowledge and experimental data. - Miltiadis Kalikatzarakis; Andrea Coraddu; Mehmet Atlar; Stefano Gaggero; Giorgio Tani; Luca Oneto (Eng. Appl. Artif. Intell., 2023)

On the problem of recommendation for sensitive users and influential items: Simultaneously maintaining interest and diversity. - Alvise De Biasio; Merylin Monaro; Luca Oneto; Lamberto Ballan; Nicolò Navarin (Knowl. Based Syst., 2023)

Do we really need a new theory to understand over-parameterization? - Luca Oneto; Sandro Ridella; Davide Anguita (Neurocomputing, 2023)

Informed Machine Learning for Complex Data. - Luca Oneto; Nicolò Navarin; Alessio Micheli; Luca Pasa; Claudio Gallicchio; Davide Bacciu; Davide Anguita (ESANN, 2024)

Mitigating Unfair Regression in Machine Learning Model Updates. - Irene Buselli; Anna Pallarès López; Eduard Martín Jiménez; Davide Anguita; Fabio Roli; Luca Oneto (ICMLA, 2024)

Toward Measuring and Understanding the Overvalidation Phenomena. - Fabrizio Mori; Antonio Emanuele Cinà; Fabio Roli; Davide Anguita; Luca Oneto (ICMLA, 2024)

Traffic Simulator AI-Based Surrogate for an Urban Road Network. - F. Cantatore; G. Raimondi; Luca Oneto; Andrea Coraddu; Cecilia Pasquale; Enrico Siri; Silvia Siri; Simona Sacone; Davide Anguita (ITSC, 2024)

Computationally Aware Surrogate Models for the Hydrodynamic Response Characterization of Floating Spar-Type Offshore Wind Turbine. - Davide Ilardi; Miltiadis Kalikatzarakis; Luca Oneto; Maurizio Collu; Andrea Coraddu (IEEE Access, 2024)

Data-Driven Models for Yacht Hull Resistance Optimization: Exploring Geometric Parameters Beyond the Boundaries of the Delft Systematic Yacht Hull Series. - Jake M. Walker; Andrea Coraddu; Luca Oneto (IEEE Access, 2024)

Over-parameterization and Adversarial Robustness in Neural Networks: An Overview and Empirical Analysis. - Zhang Chen; Luca Demetrio; Srishti Gupta; Xiaoyi Feng; Zhaoqiang Xia; Antonio Emanuele Cinà; Maura Pintor; Luca Oneto; Ambra Demontis; Battista Biggio; Fabio Roli (CoRR, 2024)

Investigating over-parameterized randomized graph networks. - Giovanni Donghi; Luca Pasa; Luca Oneto; Claudio Gallicchio; Alessio Micheli; Davide Anguita; Alessandro Sperduti; Nicolò Navarin (Neurocomputing, 2024)

Towards algorithms and models that we can trust: A theoretical perspective. - Luca Oneto; Sandro Ridella; Davide Anguita (Neurocomputing, 2024)

Fair graph representation learning: Empowering NIFTY via Biased Edge Dropout and Fair Attribute Preprocessing. - Danilo Franco; Vincenzo Stefano D'Amato; Luca Pasa; Nicolò Navarin; Luca Oneto (Neurocomputing, 2024)

Advances in artificial neural networks, machine learning and computational intelligence. - Nicolò Navarin; Dounia Mulders; Luca Oneto (Neurocomputing, 2024)

Provably Efficient and Robust Conformal Prediction under a Realistic Threat Model. - Alberto Carlevaro; Luca Oneto; Davide Anguita; Fabio Roli (COPA, 2025)

Dynamical Systems Behavior Prediction: Machine Learning and Koopman Operator. - Enrico Zero; Luca Oneto; Roberto Sacile; Davide Anguita (SoSE, 2025)

DBSCAN and DBCV application to open medical records heterogeneous data for identifying clinically significant clusters of patients with neuroblastoma. - Davide Chicco; Luca Oneto; Davide Cangelosi (BioData Min., 2025)

Informed Machine Learning: Excess risk and generalization. - Luca Oneto; Sandro Ridella; Davide Anguita (Neurocomputing, 2025)

A review on full-, zero-, and partial-knowledge based predictive models for industrial applications. - Stefano Zampini; Guido Parodi; Luca Oneto; Andrea Coraddu; Davide Anguita (Inf. Fusion, 2025)

Eight quick tips for biologically and medically informed machine learning. - Luca Oneto; Davide Chicco (PLoS Comput. Biol., 2025)

Training-Free Constrained Generation With Stable Diffusion Models. - Stefano Zampini; Jacob Christopher; Luca Oneto; Davide Anguita; Ferdinando Fioretto (CoRR, 2025)

Empirical Quantification of Spurious Correlations in Malware Detection. - Bianca Perasso; Ludovico Lozza; Andrea Ponte; Luca Demetrio; Luca Oneto; Fabio Roli (CoRR, 2025)

Robustness-Congruent Adversarial Training for Secure Machine Learning Model Updates. - Daniele Angioni; Luca Demetrio; Maura Pintor; Luca Oneto; Davide Anguita; Battista Biggio; Fabio Roli (IEEE Trans. Pattern Anal. Mach. Intell., 2025)