B006 - Donzellini, G. and Oneto, L. and Ponta, D. and Anguita. D., Springer, Introduzione al Progetto di Sistemi Digitali (2nd Edition), 2023.

B005 - Donzellini, G. and Garavagno, A. M. and Oneto, L., Springer, Introduction to microprocessor-based systems design, 2022.

B004 - Donzellini, G. and Garavagno, A. M. and Oneto, L., Springer, Introduzione al progetto di sistemi a microprocessore, 2021.

B003 - Oneto, L., Springer, Model Selection and Error Estimation in a Nutshell, 2020.

B002 - Donzellini, G. and Oneto, L. and Ponta, D. and Anguita. D., Springer, Introduction to Digital Systems Design, 2019.

B001 - Donzellini, G. and Oneto, L. and Ponta, D. and Anguita. D., Springer, Introduzione al Progetto di Sistemi Digitali, 2018.

EB003 - Coraddu, A. and Oneto, L., TU Delft OPEN Publishing, Proceedings of the 4th International Conference on Modelling and Optimisation of Ship Energy Systems (MOSES), 2024.

EB002 - Oneto, L. and Navarin, N. and Sperduti, N. and Anguita. D., Springer, Recent Trends in Learning From Data, 2020.

EB001 - Oneto, L. and Navarin, N. and Sperduti, N. and Anguita. D., Springer, Recent Advances in Big Data and Deep Learning, 2019.

BC008 - Coraddu, A. and Kalikatzarakis, M. and Walker, J. and Ilardi, D. and Oneto, L., Sustainable Energy Systems on Ships, Coraddu, A. and Baldi, F. and Mondejar, M., Elsevier, Data Science and Advanced Analytics for Shipping Energy Systems, 2022.

BC007 - Coraddu, A. and Kalikatzarakis, M. and Theotokatos, G. and Geertsma, R. and Oneto, L., Engine Modeling and Simulation, Agarwal, A. K. and Kumar, D. and Sharma, N. and Sonawane, U., Springer, Physical and Data-Driven Models Hybridisation for Modelling the Dynamic State of a Four-Stroke Marine Diesel Engine, 2020.

BC006 - Oneto, L. and Chiappa, S., Recent Trends in Learning From Data, Oneto, L. and Navarin, N. and Sperduti, N. and Anguita. D., Springer, Fairness in Machine Learning, 2020.

BC005 - Oneto, L. and Fumeo, E. and Clerico, C. and Canepa, R. and Papa, F. and Dambra, C. and Mazzino, N. and Anguita. D., Innovative Applications of Big Data in the Railway Industry, Kohli, S. and Senthil, A. V. and Easton, J. M. and Roberts, C., IGI Global, Big Data Analytics for Train Delay Prediction: A case study in the Italian Railway Network, 2017.

BC004 - Oneto, L. and Reyes-Ortiz, J. L. and Anguita, D., Adaptive Mobile Computing: Advances in Processing of Mobile Data Set, Migliardi, M. and Merlo, A. and Al-Haj Baddar, S., Elsevier, Constraint-Aware Data Analysis on Mobile Devices, 2017.

BC003 - Coraddu, A. and Oneto, L. and Baldi, F. and Anguita, D., Soft Computing for Sustainability Science. Serie Studies In Fuzziness and Soft Computing, Cruz, C., Springer, Vessels Fuel Consumption: a Data Analytics Perspective to Sustainability, 2016.

BC002 - Oneto, L. and Ridella, S. and Anguita, D., Quantum Inspired Computational intelligence: Research and Applications, Bhattacharyya, S. and Malik, U. and Dutta, P., Morgan Kaufmann, Elsevier, Quantum Computing and Supervised Machine Learning: Training, Model Selection and Error Estimation, 2016.

BC001 - Bisio, F. and Oneto, L. and Cambria, E., Sentiment Analysis in Social Networks, Pozzi, F. A. and Fersini, E. and Messina, E. and Liu, B., Elsevier, Sentic computing for social network analysis, 2016.

E007 - Oneto, L. and Schleif, F. M. and Sperduti, A., Neurocomputing, Pag:-, Advances in artificial neural networks, machine learning and computational intelligence, Vol:-, 2024.

E006 - Navarin, N. and Mulders, D. and Oneto, L., Neurocomputing, Pag:-, Advances in artificial neural networks, machine learning and computational intelligence, Vol:-, 2023.

E005 - Oneto, L. and Navarin, N. and Schleif, F. M., Neurocomputing, Pag:311-314 -  Advances in artificial neural networks, machine learning and computational intelligence, Vol:507 -  2022.

E004 - Oneto, L. and Bunte, K. and Navarin, N., Neurocomputing, Pag:300-303 -  Advances in artificial neural networks, machine learning and computational intelligence, Vol:470 -  2021.

E003 - Oneto, L. and Bunte, K. and Sperduti, A., Neurocomputing, Pag:172-176 -  Advances in artificial neural networks, machine learning and computational intelligence, Vol:416 -  2020.

E002 - Oneto, L. and Bunte, K. and Schleif, F. M., Neurocomputing, Pag:1-5 -  Advances in artificial neural networks, machine learning and computational intelligence, Vol:342 -  2019.

E001 - Aiolli, F. and Biehl, M. and Oneto, L., Neurocomputing, Pag:1-3 -  Advances in artificial neural networks, machine learning and computational intelligence, Vol:298 -  2018.

J083 - Oneto, L. and Chicco, D., PLOS Computational Biology, Pag:-, Eight quick tips for biologically and medically informed machine learning, Vol:-, 2025.

J082 - Walker, J. and Coraddu, A. and Oneto, L., Ocean Engineering, Pag:-, A Review on Shape Optimization of Hulls and Airfoils Leveraging Computational Fluid Dynamics Data-Driven Surrogate Models, Vol:-, 2024.

J081 - Donghi, G. and Pasa, L. and Oneto, L. and Gallicchio, C. and Micheli, A. and Anguita, D. and Sperduti, M. and Navarin, N., Neurocomputing, Pag:-, Investigating Over-Parameterized Randomized Graph Networks, Vol:-, 2024.

J080 - Walker, J. and Coraddu, A. and Oneto, L., IEEE Access, Num:-, Pag:-, Data-Driven Models for Yacht Hull Resistance Optimization: Exploring Geometric Parameters Beyond the Boundaries of the Delft Systematic Yacht Hull Series, Vol:-, 2024.

J079 - Oneto, L. and Ridella, S. and Anguita, D., Neurocomputing, Pag:-, Towards Algorithms and Models that We Can Trust: a Theoretical Perspective, Vol:-, 2024.

J078 - Coraddu, A. and Oneto, L. and Walker, J. and Patryniak, K. and Prothero, A. and Collu, M., Mechanical Systems and Signal Processing, Num:-, Pag:-, Floating Offshore Wind Turbine Mooring Line Sections Health Status Nowcasting: from Supervised Shallow to Weakly Supervised Deep Learning, Vol:-, 2024.

J077 - Ilardi, D. and  Kalikatzarakis, M. and Oneto, L. and Collu, M. and Coraddu, A., IEEE Access, Pag:-, Computationally Aware Surrogate Models for the Hydrodynamic Response Characterisation of Floating Spar-Type Offshore Wind Turbine, Vol:-, Num:-, 2023.

J076 - Franco, D. and D'Amato, V. S. and Pasa, L. and Navarin, N. and Oneto, L., Neurocomputing, Pag:126948 -  Fair graph representation learning: Empowering NIFTY via Biased Edge Dropout and Fair Attribute Preprocessing, Vol:563 -  2023.

J075 - Cecchetti, G. and Ruscelli, A. L. and Ulianov, C. and Hyde, P. and Magnien, A. and Oneto, L. and Bertolin, J., Transportation Engineering, Pag:100222 -  A Communication Platform Demonstrator for new generation railway Traffic Management Systems: testing and validation, Vol:15 -  2023.

J074 - Coraddu, A. and Oneto, L. and Li, S. and Kalikatzarakis, M. and Karpenko, O., Engineering Structures, Pag:116645 -  Surrogate Models to Unlock the Optimal Design of Stiffened Panels Accounting for Ultimate Strength Reduction due to Welding Residual Stress, Vol:293 -  2023.

J073 - De Biasio, A. and Monaro, M. and Oneto, L. and Ballan, L. and Navarin, N., Knowledge-Based Systems, Pag:110699 -  On the Problem of Recommendation for Sensitive Users and Influential Items: Simultaneously Maintaining Interest and Diversity, Vol:275 -  2023.

J072 - Cademartori, G. and Oneto, L. and Valdenazzi, F. and Coraddu, A. and Gambino, A. and Anguita, D., Ocean Engineering, Pag:114822 -  A Review on Ship Motions and Quiescent Periods Prediction Models, Vol:280 -  2023.

J071 - Oneto, L. and Ridella, S. and Anguita, D., Neurocomputing, Pag:126227 -  Do We Really Need a New Theory to Understand Over-Parameterization?, Vol:543 -  2023.

J070 - Chicco, D. and Oneto, L. and Tavazzi, E., PLoS Computational Biology, Num:12 -  Pag:e1010718 -  Eleven quick tips for data cleaning and feature engineering, Vol:18 -  2022.

J069 - Kalikatzarakis, C. and Coraddu, A. and Atlar, M. and Gaggero, S. and Tani, G. and Oneto, L., Engineering Applications of Artificial Intelligence, Pag:105660 -  Physically plausible propeller noise prediction via recursive corrections leveraging prior knowledge and experimental data, Vol:118 -  2023.

J068 - Oneto, L. and Ridella, S. and Anguita, D., Neurocomputing, Pag:125-141 -  The Benefits of Adversarial Defense in Generalization, Vol:505 -  2022.

J067 - Li, S. and Coraddu, A. and Oneto, L., Engineering Structures, Pag:114423 -  Computationally Aware Estimation of Ultimate Strength Reduction of Stiffened Panels Caused by Welding Residual Stress: from Finite Element to Data-Driven Methods, Vol:264 -  2022.

J066 - Barco, S. and Lavarello, C. and Cangelosi, D. and Morini, M. and Eva, A. and Oneto, L. and Uva, P. and Tripodi, G. and Garaventa, A. and Conte, M. and Petretto, A. and Cangemi, G., Frontiers in Oncology, Pag:845936 -  Untargeted LC-HRMS based-plasma metabolomics reveals 3-O-methyldopa as a new biomarker of poor prognosis in high-risk neuroblastoma, Vol:12 -  2022.

J065 - Olugbade, T. and Bienkiewicz, M. and Barbareschi, G. and D'Amato, V. and Oneto, L. and Camurri, A. and Holloway, C. and Bjorkman, M. and Keller, P. and Clayton, M. and Williams, A. and Gold, N. and Becchio, C. and Bardy, B. and Bianchi-Berthouze, N., ACM Computing Surveys, Num:6 -  Pag:1-29 -  Human Movement Datasets: An Interdisciplinary Scoping Review, Vol:55 -  2022.

J064 - Kalikatzarakis, M. and Coraddu, A. and Atlar, M. and Gaggero, S. and Tani, G. and Villa, D. and Oneto, L., Ocean Engineering, Pag:111477 -  Computational prediction of underwater radiated noise of cavitating marine propellers: on the accuracy of semi-empirical models, Vol:259 -  2022.

J063 - Oneto, L. and Navarin, N. and Biggio, B. and Errica, F. and Micheli, A. and Scarselli, F. and Bianchini, M. and Demetrio, L. and Bongini, P. and Tacchella, A. and Sperduti, A., Neurocomputing, Pag:217-243 -  Towards Learning Trustworthily, Automatically, and with Guarantees on Graphs: an Overview, Vol:493 -  2022.

J062 - Buselli, I. and Oneto, L. and Dambra, . and Gallego, C. V. and Martinez, M. G. and Smoker, A. and Ike, N. and Pejovic, T. and Martino, P. R., Open Research Europe, Pag:110 -  Natural language processing for aviation safety: extracting knowledge from publicly-available loss of separation reports, Vol:1 -  2022.

J061 - Valchev, I. and Coraddu, A. and Kalikatzarakis, M. and Geertsma, R. and Oneto, L., Ocean Engineering, Pag:110883 -  Numerical methods for monitoring and evaluating the biofouling state and effects on vessels' hull and propeller performance: A review, Vol:251 -  2022.

J060 - Chicco, D. and Lovejoy, C. A. and Oneto, L., IEEE Access, Pag:165132-165144 -  A machine learning analysis of health records of patients with chronic kidney disease at risk of cardiovascular disease, Vol:9 -  2021.

J059 - Walker, J. and Coraddu, A. and Collu, M. and Oneto, L., Journal of Ocean Engineering and Marine Energy, Pag:1-16 -  Digital Twins of the Mooring Line Tension for Floating Offshore Wind Turbines to Improve Monitoring, Lifespan, and Safety, Vol:8 -  2021.

J058 - Franco, D. and Oneto, L. and Navarin, N. and Anguita, D., Entropy, Num:8 -  Pag:1047 -  Toward Learning Trustworthily from Data Combining Privacy, Fairness, and Explainability: an Application to Face Recognition, Vol:23 -  2021.

J057 - Franco, D. and Navarin, N. and Donini, M. and Anguita, D. and Oneto, L., Neurocomputing, Pag:318-334 -  Deep Fair Models for Complex Data: Graphs Labeling and Explainable Face Recognition, Vol:470 -  2021.

J056 - Coraddu, A. and Oneto, L. and Cipollini, F. and Kalikatzarakis, M. and Meijn, G. J. and Geertsma, R., Ships and Offshore Structures, Num:6 -  Pag:1360-1381 -  Physical, Data-Driven, and Hybrid Approaches to Model Engine Exhaust Gas Temperatures in Operational Conditions, Vol:17 -  2021.

J055 - Coraddu, A. and Oneto, L. and Ilardi, D. and Stoumpos, S. and Theotokatos, G., Engineering Applications of Artificial Intelligence, Pag:104179 -  Marine Dual Fuel Engines Monitoring In The Wild through Weakly Supervised Data Analytics, Vol:100 -  2021.

J054 - Oneto, L. and Ridella, S., Entropy, Num:1 -  Pag:101 -  Distribution Dependent Weighted Union Bound, Vol:23 -  2021.

J053 - Chicco, D. and Oneto, L., BioData Mining, Num:12 -  Pag:1-22 -  Data analytics and clinical feature ranking of medical records of patients with sepsis, Vol:14 -  2021.

J052 - Chicco, D. and Oneto, L., Health Informatics Journal, Num:1 -  Pag:1460458220984205 -  Computational intelligence identifies alkaline phosphatase (ALP), alpha-fetoprotein (AFP), and hemoglobin levels as most predictive survival factors for hepatocellular carcinoma, Vol:27 -  2021.

J051 - Chicco, D. and Oneto, L., IEEE/ACM Transactions on Computational Biology and Bioinformatics, Num:6 -  Pag:2759-2765 -  An enhanced Random Forests approach to predict heart failure from small imbalanced gene expression data, Vol:18 -  2020.

J050 - Kalikatzarakis, M. and Coraddu, A. and Oneto, L. and Anguita, D., IEEE Transactions on Automation Science and Engineering, Num:1 -  Pag:122-142 -  Optimising Fuel Consumption in Thrust Allocation for Marine Dynamic Positioning Systems, Vol:19 -  2020.

J049 - D'Amato, V. and Volta E. and Oneto, L. and Volpe, G. and Camurri, A. and Anguita D., Cognitive Computation, Pag:1356-1369 -  Understanding Violin Players Skills Level based on Motion Capture: a Data Driven Perspective, Vol:12 -  2020.

J048 - Ponta, L. and Puliga, G. and Oneto, L. and Manzini, R., IEEE Transactions on Engineering Management, Num:5 -  Pag:2144-2154 -  Identifying the determinants of innovation capability with machine learning: how patents can be predictive, Vol:69 -  2020.

J047 - Coraddu, A and Oneto, L. and Navas de Maya, B. and Rafet, K., Ocean Engineering, Pag:107588 -  Determining the Most Influential Human Factors in Maritime Accidents: a Data-Driven Approach, Vol:211 -  2020.

J046 - Miglianti, L. and Cipollini, F. and Oneto, L. and Tani, G. and Gaggero, S. and Coraddu, A. and Viviani, M., Ocean Engineering, Pag:107481 -  Predicting the Cavitating Marine Propeller Noise at Design Stage: a Deep Learning Based Approach, Vol:209 -  2020.

J045 - Oneto, L. and Donini, M. and Pontilc, M. and Shawe-Taylor, J., Neurocomputing, Pag:231-243 -  Randomized Learning and Generalization of Fair and Private Classifiers: from PAC-Bayes to Stability and Differential Privacy, Vol:416 -  2020.

J044 - Oneto, L., Intelligenza Artificiale, Num:1 -  Pag:151-178 -  Learning Fair Models and Representations, Vol:14 -  2020.

J043 - Picasso, A. and Merello, S. and Ma, Y. and Oneto, L. and Cambria, E., Expert Systems With Applications, Pag:60-70 -  Technical Analysis and Sentiment Embeddings for Market Trend Prediction, Vol:135 -  2019.

J042 - Coraddu, A. and Oneto, L. and Baldi, F. and Cipollini, F. and Atlar, M. and Savio, S., Ocean Engineering, Pag:106063 -  Data-Driven Ship Digital Twin for Estimating the Speed Loss caused by the Marine Fouling, Vol:186 -  2019.

J041 - Carrega, A. and Cipollini, F. and Oneto, L., Neurocomputing, Pag:91-104 -  Simple Continuous Optimal Regions of the Space of Data, Vol:349 -  2019.

J040 - Miglianti, F. and Cipollini, F. and Oneto, L. and Tani, G. and Viviani, M., Ocean Engineering, Pag:185-203 -  Model Scale Cavitation Noise Spectra Prediction: Combining Physical Knowledge with Data Science, Vol:178 -  2019.

J039 - Coraddu, A. and Lim, S. and Oneto, L. and Pazouki, K. and Norman, R. and Murphy, A. J., Ocean Engineering, Pag:65-73 -  A novelty detection approach to diagnosing hull and propeller fouling, Vol:176 -  2019.

J038 - Oneto, L. and Buselli, I. and Lulli, A. and Canepa, R. and Petralli, S. and Anguita, D., International Journal of Data Science and Analytics, Num:1 -  Pag:95-111 -  A Dynamic, Interpretable, and Robust Hybrid Data Analytics System for Train Movements in Large-Scale Railway Networks, Vol:9 -  2019.

J037 - Cipollini, F. and Oneto, L. and Coraddu, A. and Savio. S., Data-Enabled Discovery and Applications, Num:1 -  Unsupervised Deep Learning for Induction Motors Bearings Monitoring, Vol:3 -  2018.

J036 - Lulli, A. and Oneto, L. and Anguita, D., Cognitive Computation, Num:2 -  Pag:294-316 -  Mining Big Data with Random Forests, Vol:11 -  2018.

J035 - Oneto, L. and Ridella, S. and Anguita, D., Neurocomputing, Pag:24-32 -  Local Rademacher Complexity Machine, Vol:342 -  2019.

J034 - Oneto, L. and Coraddu, A. and Cipollini, F. and Karpenko, O. and Xepapa, K. and Sanetti, P. and Anguita, D., Data-Enabled Discovery and Applications, Num:11 -  Crash Stop Manoeuvring Performance Prediction: a Data Driven Solution for Safety and Collision Avoidance, Vol:2 -  2018.

J033 - Cipollini, F. and Oneto, L. and Coraddu, A. and Murphy, A. J. and Anguita, D., Reliability Engineering & System Safety, Pag:12-23 -  Condition-Based Maintenance of Naval Propulsion Systems: Data Analysis with Minimal Feedback, Vol:177 -  2018.

J032 - Oneto, L., Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, Num:4 -  Model Selection and Error Estimation Without the Agonizing Pain, Vol:8 -  2018.

J031 - Cipollini, F. and Oneto, L. and Coraddu, A and Murphy, A. J. and Anguita, D., Ocean Engineering, Pag:268-278 -  Condition-Based Maintenance of Naval Propulsion Systems with Supervised Data Analysis, Vol:149 -  2018.

J030 - Oneto, L. and Navarin, N. and Donini, M. and Ridella, S. and Sperduti, A. and Aiolli, F. and Anguita, D., IEEE Transactions on Neural Networks and Learning Systems, Num:10 -  Pag:4660-4671 -  Learning with Kernels: A Local Rademacher Complexity-based Analysis with Application to Graph Kernels, Vol:29 -  2018.

J029 - Oneto, L. and Cipollini, F. and Ridella, S. and Anguita, D., Neurocomputing, Pag:21-33 -  Randomized Learning: Generalization Performance of Old and New Theoretically Grounded Algorithms, Vol:298 -  2018.

J028 - Aonzo, S. and Merlo, A. and Migliardi, M. and Oneto, L. and Palmieri, F., IEEE Transactions on Sustainable Computing, Num:2 -  Pag:213-222 -  Low-Resource Footprint, Data-Driven Malware Detection on Android, Vol:5 -  2020.

J027 - Oneto, L. and Navarin, N. and Sperduti, A. and Anguita, D., Neural Processing Letters, Num:2 -  Pag:649-667 -  Multilayer Graph Node Kernels: Stacking while Maintaining Convexity, Vol:48 -  2017.

J026 - Oneto, L. and Fumeo, E. and Clerico, C. and Canepa, R. and Papa, F. and Dambra, C. and Mazzino, N. and Anguita. D., Big Data Research, Pag:54-64 -  Train Delay Prediction Systems: a Big Data Analytics Perspective, Vol:11 -  2018.

J025 - Oneto, L. and Fumeo, E. and Clerico, C. and Canepa, R. and Papa, F. and Dambra, C. and Mazzino, N. and Anguita. D., IEEE Transactions on Systems, Man and Cybernetics: Systems, Num:10 -  Pag:2754-2767 -  Dynamic Delay Predictions for Large-Scale Railway Networks: Deep and Shallow Extreme Learning Machines Tuned via Thresholdout, Vol:47 -  2017.

J024 - Oneto, L. and Navarin, N. and Donini, M. and Sperduti, A. and Aiolli, F. and Anguita, D., Neurocomputing, Pag:4-16 -  Measuring the Expressivity of Graph Kernels through Statistical Learning Theory, Vol:268 -  2017.

J023 - Oneto, L. and Laureri, F. and Robba, M. and Delfino, F. and Anguita, D., IEEE System Journal, Num:3 -  Pag:2842-2853 -  Data-Driven Photovoltaic Power Production Nowcasting and Forecasting for Polygeneration Microgrids, Vol:12 -  2017.

J022 - Oneto, L. and Ridella, S. and Anguita, D., Pattern Recognition Letters, Pag:31-38 -  Differential privacy and generalization: Sharper bounds with applications, Vol:89 -  2017.

J021 - Coraddu, A. Oneto, L. and Baldi, F. and Anguita, D., Ocean Engineering, Pag:351-370 -  Vessels Fuel Consumption Forecast and Trim Optimisation: a Data Analytics Perspective, Vol:130 -  2017.

J020 - Oneto, L. and Bisio, F. and Cambria, E. and Anguita, D., Cognitive Computation, Num:2 -  Pag:259-274 -  SLT-Based ELM for Big Social Data Analysis, Vol:9 -  2017.

J019 - Oneto, L. and Bisio, F. and Cambria, E. and Anguita, D., Cognitive Computation, Num:1 -  Pag:18-42 -  Semi-supervised Learning for Affective Common-Sense Reasoning, Vol:9 -  2017.

J018 - Oneto, L. and Bisio, F. and Cambria, E. and Anguita, D., IEEE Computational Intelligence Magazine, Num:3 -  Pag:45-55 -  Statistical Learning Theory and ELM for Big Social Data Analysis, Vol:11 -  2016.

J017 - Oneto, L. and Anguita, D. and Ridella, S., Pattern Recognition Letters, Pag:200-207 -  PAC-bayesian analysis of distribution dependent priors: Tighter risk bounds and stability analysis, Vol:80 -  2016.

J016 - Oneto, L. and Anguita, D. and Ridella, S., Neural Networks, Pag:62-75 -  A local Vapnik-Chervonenkis complexity, Vol:82 -  2016.

J015 - Oneto, L. and Ridella, S. and Anguita, D., Machine Learning, Num:1 -  Pag:103-136 -  Tikhonov, Ivanov and Morozov regularization for support vector machine learning, Vol:103 -  2015.

J014 - Oneto, L. and Ridella, S. and Anguita, D., ACM Transaction on Embedded Computing, Num:2 -  Pag:23:1-23:29 -  Learning Hardware-Friendly Classifiers through Algorithmic Stability, Vol:15 -  2016.

J013 - Vahdat, M. and Oneto, L. and Anguita, D. and Funk, M. and Rauterberg, M., Neurocomputing, Pag:14-28 -  Can Machine Learning explain Human Learning?, Vol:192 -  2016.

J012 - Reyes-Ortiz, J. L. and Oneto, L. and Sama, A. and Parra, X. and Anguita, D., Neurocomputing, Pag:754-767 -  Transition-Aware Human Activity Recognition Using Smartphones, Vol:171 -  2016.

J011 - Oneto, L. and Ghio, A. and Ridella, S. and Anguita, D., Neural Processing Letters, Num:2 -  Pag:567-602 -  Global Rademacher Complexity Bounds: From Slow to Fast Convergence Rates, Vol:43 -  2015.

J010 - Oneto, L. and Ghio, A. and Ridella, S. and Anguita, D., Neural Networks, Pag:115-125 -  Local Rademacher Complexity: Sharper Risk Bounds With and Without Unlabeled Samples, Vol:65 -  2015.

J009 - Oneto, L. and Ghio, A. and Ridella, S. and Anguita, D., Neurocomputing, Pag:225-235 -  Learning Resource-Aware Models for Mobile Devices: from Regularization to Energy Efficiency, Vol:169 -  2015.

J008 - Oneto, L. and Ghio, A. and Ridella, S. and Anguita, D., IEEE Transactions on Cybernetics, Num:9 -  Pag:1913-1926 -  Fully Empirical and Data-Dependent Stability-Based Bounds, Vol:45 -  2015.

J007 - Coraddu, A. and Oneto, L. and Ghio, A. and Savio, S. and Anguita, D. and Figari, M., Proceedings of the Institution of Mechanical Engineers Part M: Journal of Engineering for the Maritime Environment, Num:1 -  Pag:136-153 -  Machine learning approaches for improving condition-based maintenance of naval propulsion plants, Vol:230 -  2016.

J006 - Anguita, D. and Ghio, A. and Oneto, L. and Ridella, S., IEEE Transactions on Neural Networks and Learning Systems, Num:12 -  Pag:2202-2211 -  A Deep Connection Between the Vapnik-Chervonenkis Entropy and the Rademacher Complexity, Vol:25 -  2014.

J005 - Anguita, D. and Ghio, A. and Oneto, L. and Ridella, S., Pattern Recognition Letters, Pag:210-219 -  Unlabeled patterns to tighten Rademacher complexity error bounds for kernel classifiers, Vol:37 -  2014.

J004 - Oneto, L. and Ghio, A. and Anguita, D. and Ridella, S., Neural Networks, Pag:107-111 -  An improved analysis of the Rademacher data-dependent bound using its self bounding property, Vol:44 -  2013.

J003 - Anguita, D. and Ghio, A. and Oneto, L. and Parra, X. and Reyes-Ortiz, J. L., Journal of Universal Computer Science, Num:9 -  Pag:1295-1314 -  Energy Efficient Smartphone-Based Activity Recognition using Fixed-Point Arithmetic., Vol:19 -  2013.

J002 - Anguita, D. and Ghio, A. and Oneto, L. and Ridella, S., Neural processing letters, Num:3 -  Pag:275-283 -  In-sample model selection for trimmed hinge loss support vector machine, Vol:36 -  2012.

J001 - Anguita, D. and Ghio, A. and Oneto, L. and Ridella, S., IEEE Transactions on Neural Networks and Learning Systems, Num:9 -  Pag:1390-1406 -  In-sample and out-of-sample model selection and error estimation for support vector machines, Vol:23 -  2012.

C140 - Petrocco, E. U. and Sgorbissa, A. and Oneto, L., Italian Conference on Robotics and Intelligent Machines, The Impact of Data Augmentation and Oversampling on Cultural Competence in Social Robotics, 2024.

C139 - Buselli, I. and López, A. P. and Jiménez, E. M. and  Anguita, D. and Roli, F. and Oneto, L., International Conference on Machine Learning and Applications (ICMLA), Mitigating Unfair Regression in Machine Learning Model Updates, 2024.

C138 - Mori, F. and Cinà, A. E. and Roli, F. and Anguita, D. and Oneto, L., International Conference on Machine Learning and Applications (ICMLA), Toward Measuring and Understanding the Overvalidation Phenomena, 2024.

C137 - Cantatore, F. and Raimondi, G. and Oneto, L. and Coraddu, A. and Pasquale, C. C. and Siri, E. and Siri, S. and Sacone, S. and Anguita, D., IEEE International Conference on Intelligent Transportation Systems (ITSC), Traffic Simulator AI-based Surrogate for an Urban Road Network, 2024.

C136 - Oneto, L. and Ridella, S. and Anguita, D., European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), Informed Machine Learning: Excess Risk and Generalization, 2024.

C135 - Oneto, L. and Navarin, N. and Micheli, A. and Pasa, L. and Gallicchio, C. and Bacciu, D. and Anguita, D., European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), Informed Machine Learning for Complex Data, 2024.

C134 - Parodi, G. and Oneto, L. and Coraddu, A. and Ferro, G. and Zampini, S. and Robba, M. and Anguita, D., IEEE Symposium Series on Computational Intelligence (SSCI), Physics Informed Data Driven Techniques for Power Flow Analysis, 2023.

C133 - Walker, J. M. and Coraddua, A. and Savio, S. and Oneto, L., International Conference on Modelling and Optimisation of Ship Energy Systems (MOSES), Shallow and Deep Learning Models for Vessel Motions Forecasting during Adverse Weather Conditions, 2023.

C132 - Petrocco, E. U. and Sgorbissa, A. and Oneto, L., Italian Conference on Robotics and Intelligent Machines, Culture-Competent Machine Learning in Social Robotics, 2023.

C131 - Graziano, D. and Ucci, D. and Bisio, F. and Oneto, L., International Conference on Optimization, Learning Algorithms and Applications (OL2A), PhishVision: a Deep Learning based Visual Brand Impersonation Detector for Identifying Phishing Attacks, 2023.

C130 - Giampaoli, D. and Cipollini, F. and Maffione, D. and Oneto, L., IEEE International Conference on Data Science and Advanced Analytics (DSAA), Short-term Forecast and Long-term Simulation for Accurate Energy Consumption Prediction, 2023.

C129 - Oneto, L. and Ridella, S. and Anguita, D., European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), Towards Randomized Algorithms and Models that We Can Trust: a Theoretical Perspective, 2023.

C128 - Franco, D. and Oneto, L. and Anguita, D., European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), Mitigating Robustness Bias: Theoretical Results and Empirical Evidences, 2023.

C127 - Ceni, A. and Bacciu, D. and De Caro, V. and Gallicchio, C. and Oneto, L., European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), Improving Fairness via Intrinsic Plasticity in Echo State Networks, 2023.

C126 - Navarin, N. and Pasa, L. and Oneto, L. and Sperduti, A., European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), An Empirical Study of Over-Parameterized Neural Models based on Graph Random Features, 2023.

C125 - Coraddu, A. and Gaggero, S. and Villa, D. and Oneto, L., International Conference on Computational Methods in Marine Engineering (MARINE), A Non-Deterministic Propeller Design Optimization Framework Leveraging Machine Learning Based Boundary Element Methods Surrogates, 2023.

C124 - Walker, J. and Coraddu, A. and Oneto, L., International Conference on Computer Applications and Information Technology in the Maritime Industries (COMPIT), A Decoupled Approach to AI-based Design and Optimization of the Delft Systematic Yacht Hull Series, 2023.

C123 - Franco, D. and Oneto, L. and Anguita, D., International Work-Conference on Artificial and Natural Neural Networks (IWANN), Fair Empirical Risk Minimization Revised, 2023.

C122 - Pinasco, S. and Lagomarsino, S. and Carocci, C. and Coraddu, A. and Oneto, L. and Cattari, S., International Conference on Computational Methods in Structural Dynamics and Earthquake Engineering (COMPDYN), Machine learning-based identification of vulnerability factors for masonry buildings in aggregate: the  historical centre of Casentino hit by the 2009 L’Aquila earthquake, 2023.

C121 - Valchev, I. and Coraddu, A. and Oneto, L. and Kalikatzarakis, M. and Tiddens, W. and Geertsma, R. D., International Ship Control Systems Symposium, Artificial Intelligence-based short-term forecasting of vessel performance parameters, 2022.

C120 - Walker, J. M. and Coraddua, A. and Garofanoa, V. and Oneto, L., International Ship Control Systems Symposium, Artificial Intelligence Based Short-Term Motions Forecasting for Autonomous Marine Vehicles Control, 2022.

C119 - Demutti, M. and D'Amato, V. and Recchiuto, C. T. and Oneto, L. and Sgorbissa, A., Italian Workshop on Artificial Intelligence and Robotics, A Cloud Architecture for Emotion Recognition Based on the Appraisal Theory, 2022.

C118 - Gjaci, A. and Oneto, L. and Recchiuto, C. T. and Sgorbissa, A., Italian Workshop on Artificial Intelligence and Robotics, Culture Awareness in Intelligent Systems, 2022.

C117 - Kalikatzarakis, M. and Coraddu, A. and Atlar, M. and Gaggero, S. and Tani, G. and Oneto,  L., Symposium on Naval Hydrodynamics (SNH), Data-driven Underwater Radiated Noise Modelling of Cavitating Marine Propellers, 2022.

C116 - Oneto, L. and Ridella, S. and Anguita, D., European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), Do We Really Need a New Theory to Understand the Double-Descent?, 2022.

C115 - Caldart, F. and Pasa, L. and Oneto, L. and Sperduti, A. and Navarin, N., European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), Biased Edge Dropout in NIFTY for Fair Graph Representation Learning, 2022.

C114 - Minisi, S. and Garrone, A. and Oneto, L. and Canepa, R. and Dambra, C. and Anguita, D., European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), Simple Non Regressive Informed Machine Learning Model for Predictive Maintenance of Railway Critical Assets, 2022.

C113 - Garrone, A. and Minisi, S. and Oneto, L. and Dambra, C. and Borinato, M. and Sanetti, P. and Vignola, G. and Papa, F. and Mazzino, N. and Anguita, D., International Conference on System-Integrated Intelligence. Intelligent, flexible and connected systems in products and production (SysInt), Simple Non Regressive Informed Machine Learning Model for Prescriptive Maintenance of Track Circuits in a Subway Environment, 2022.

C112 - Buselli, I. and Oneto, L. and Dambra, C. and Gallego, C. V. and Martinez, M. G., International Conference on System-Integrated Intelligence. Intelligent, flexible and connected systems in products and production (SysInt), Data-Driven Methods for Aviation Safety: from Data to Knowledge, 2022.

C111 - Dodaro, C. and Ilardi, D. and Oneto, L. and Ricca, F., International Conference on Logic Programming and Non-monotonic Reasoning (LPNMR), Deep learning for the generation of heuristics in answer set programming: a case study of graph coloring, 2022.

C110 - Demutti, M. and D'Amato, V. and Recchiuto, C. T. and Oneto, L. and Sgorbissa, A., IEEE International Conference on Robot and Human Interactive Communication (RO-MAN), Assessing Emotions in Human-Robot Interaction Based on the Appraisal Theory, 2022.

C109 - D'Amato, V. and Oneto, L. and Camurri, A. and Anguita, D. and Zarandi, Z. and Fadiga, L. and D'Ausilio, A. and Pozzo, T., IEEE International Joint Conference on Neural Networks (IJCNN), The Importance of Multiple Temporal Scales in Motion Recognition: from Shallow to Deep Multi Scale Models, 2022.

C108 - D'Amato, V. and Oneto, L. and Camurri, A. and Anguita, D., IEEE International Joint Conference on Neural Networks (IJCNN), The Importance of Multiple Temporal Scales in Motion Recognition: when Shallow Model can Support Deep Multi Scale Models, 2022.

C107 - Gogos, S. and Oneto, L. and Anastasopoulos, M. and Anguita, D. and Baroni, I. and Canepa, R. and Petralli, S. and Dambra, C. and Jentner, W., Transport Research Arena Conference Lisbon, DAYDREAMS - Development of Prescriptive Analytics based on Artificial Intelligence for Railways Intelligent Asset Management Systems, 2022.

C106 - Cecchetti, G. and Ruscelli, A. L. and Ulianov, C. and Hyde, P. and Liu, J. and Magnien, A. and Tavac, M. and Duracik, M. and Oneto, L. and Bertolin, J., Transport Research Arena Conference Lisbon, Toward new generation railway Traffic Management Systems: the contribution of the OPTIMA project, 2022.

C105 - Hunt, G. and Coraddu, A. and Oneto, L. and Cammarano, A., Machine Learning and Data Assimilation for Dynamical Systems (MLDADS) workshop at the International Conference on Computational Science (ICCS), Machine Learning based surrogate models for COVID-19 infection risk assessment, 2022.

C104 - Buselli, I. and Oneto, L. and Dambra, C. and Gallego, C. V. and Martinez, M. G. and Smoker, A. and Ike, N. and Martino, P. R. and Pejovic, T., SESAR Innovation Days (SIDs), Natural Language Processing and Data-Driven Methods for Aviation Safety and Resilience: from Extant Knowledge to Potential Precursors, 2021.

C103 - Barco, S. and Lavarello, C. and Petretto, A. and Oneto, L. and Morini, M. and Eva, A. and Cangelosi, D. and Montalto, S. and Conte, M. and Garaventa, A. and Tripodi, G. and Cangemi, G., International Congress of Paediatric Laboratory Medicine (ICPLM), High resolution mass spectrometry metabolomic combined with machine learning is a useful approach for risk stratification in neuroblastoma, 2021.

C102 - D'Amato, V. and Oneto, L. and Camurri, A. and Anguita, D., International Conference on Affective Computing & Intelligent Interaction (ACII) Workshop - Affective Movement Recognition Challenge and Workshop, Keep it Simple: Handcrafting Feature and Tuning Random Forests and XGBoost to face the Affective Movement Recognition Challenge 2021 -  2021.

C101 - Cordero, J. M. and Garcia-Ovies, I. and Iglesias, E. and Dambra, C. and Buselli, I. and Oneto, L. and Abate, C. and Pozzi, S. and Sanz, A. R., SESAR Innovation Days (SIDs), Traffic Characterization for a Dynamic and Adaptive Trajectory Prediction Data-Driven Approach, 2020.

C100 - Walker, J. and Coraddu, A. and Oneto, L. and Kilbourn, S., Global OCEANS 2021 (OCEANS), Digital Twin of the Mooring Line Tension for Floating Offshore Wind Turbines, 2021.

C099 - Cecchetti, G. and Ruscelli, A. L. and Castoldi, P. and Ulianov, C. and Hyde, P. and Oneto, L. and Marton, P., Euro Working Group on Transportation Meeting (EWGT), Communication platform concept for virtual testing of novel applications for railway traffic management systems, 2021.

C098 - Oneto, L. and Navarin, N. and Biggio, B. and Errica, F. and Micheli, A. and Scarselli, F. and Bianchini, M. and Sperduti, A., European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), Complex Data: Learning Trustworthily, Automatically, and with Guarantees, 2021.

C097 - Oneto, L. and Ridella, S. and Anguita, D., European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), The Benefits of Adversarial Defence in Generalisation, 2021.

C096 - Boleto, G. and Oneto, L. and Cardellini, M. and Maratea, M. and Vallati, M. and Canepa, R. and Anguita, D., European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), In-Station Train Movements Prediction: from Shallow to Deep Multi Scale Models, 2021.

C095 - D'Amato, V. and Volta, E. and Oneto, L. and Volpe, G. and Camurri, A. and Anguita, D., International Work-Conference on Artificial and Natural Neural Networks (IWANN), Accuracy and Intrusiveness in Data-Driven Violin Players Skill Levels Prediction: MOCAP against MYO against KINECT, 2021.

C094 - Kalikatzarakis, M. and Coraddu A. and Atlar, M. and Tani, G. and Gaggero, S. and Villa, D. and Oneto, L., Conference on Computational Methods in Marine Engineering (Marine), Computational Prediction of Propeller Cavitation Noise, 2021.

C093 - Kalikatzarakis, M. and Coraddu A. and Theotokatos, G. and Oneto, L., International Conference on Modelling and Optimisation of Ship Energy Systems (MOSES), Development of a zero-dimensional model and application on a medium-speed marine four-stroke diesel engine, 2021.

C092 - Franco, D. and Oneto, L. and Navarin, N. and Anguita, D., IEEE International Joint Conference on Neural Networks (IJCNN), Learn and Visually Explain Deep Fair Models: an Application to Face Recognition, 2021.

C091 - Cardellini, M. and Maratea, M. and Vallati, M. and Boleto, G. and Oneto, L., International Symposium on Combinatorial Search (SoCS), A Planning-based Approach for In-Station Train Dispatching, 2021.

C090 - Cardellini, M. and Maratea, M. and Vallati, M. and Boleto, G. and Oneto, L., International Conference on Computational Science (ICCS), An Efficient Hybrid Planning Framework for In-Station Train Dispatching, 2021. 

C089 - Cardellini, M. and Maratea, M. and Vallati, M. and Boleto, G. and Oneto, L., International Conference on Automated Planning and Scheduling (ICAPS), In-Station Train Dispatching: a PDDL+ Planning Approach, 2021.

C088 - Chzhen, E. and Hebiri, H. and Denis, C. and Oneto, L. and Pontil, M., Advances in Neural Information Processing Systems (NIPS), Fair Regression with Wasserstein Barycenters, 2020.

C087 - Chzhen, E. and Denis, C. and Hebiri, H. and Oneto, L. and Pontil, M., Advances in Neural Information Processing Systems (NIPS), Fair Regression via Plug-In Estimator and Recalibration, 2020.

C086 - Oneto, L. and Donini, M. and Luise, G. and Ciliberto, C. and Maurer, A. and Pontil, M., Advances in Neural Information Processing Systems (NIPS), Exploiting MMD and Sinkhorn Divergences for Fair and Transferable Representation Learning, 2020.

C085 - Coraddu, A. and Oneto, L. and Kalikatzarakis, M. and Ilardi, D. and Collu, M., OCEANS 2020: Singapore-U.S. Gulf Coast, Floating Spar-Type Offshore Wind Turbine Hydrodynamic Response Characterisation: a Computational Cost Aware Approach, 2020.

C084 - Oneto, L. and Donini, M. and Pontil, M. and Maurer, A., IEEE International Conference on Data Science and Advanced Analytics (DSAA), Learning Fair and Transferable Representations with Theoretical Guarantees, 2020.

C083 - Oneto, L. and Donini, M. and Pontil, M., IEEE International Joint Conference on Neural Networks (IJCNN), General Fair Empirical Risk Minimization, 2020.

C082 - Navarin, N. and Cambiaso, M. and Burattin, A. and Maggi, F. M. and Oneto, L. and Sperduti, A., IEEE International Joint Conference on Neural Networks (IJCNN), Towards Online Discovery of Data-Aware Declarative Process Models from Event Streams, 2020.

C081 - Oneto, L. and Cipollini, F. and Miglianti, L. and Tani, G. and Gaggero, S. and Coraddu, A. and Viviani, M., IEEE International Joint Conference on Neural Networks (IJCNN), Deep Learning for Cavitating Marine Propeller Noise Prediction at Design Stage, 2020.

C080 - Navarin, N. and Oneto, L. and Donini, M., European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), Learning Deep Fair Graph Neural Networks, 2020.

C079 - Oneto, L. and Ridalla, S. and Anguita, D., European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), Improving the Union Bound: a Distribution Dependent Approach, 2020.

C078 - Consilvio, A. and Sanetti, P. and Anguita, D. and Crovetto, C. and Dambra, C. and Oneto, L. and Papa, F. and Sacco, N., International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS), Prescriptive Maintenance of Railway Infrastructure: From Data Analytics to Decision Support, 2019.

C077 - Chzhen, E. and Hebiri, H. and Denis, C. and Oneto, L. and Pontil, M., Advances in Neural Information Processing Systems (NIPS), Leveraging Labeled and Unlabeled Data for Consistent Fair Binary Classification, 2019.

C076 - Manzini, R. and Oneto, L. and Ponta, L. and Puliga, G. and Noe, C., SEFI Annual Conference (SEFI), Studying innovation with patents and machine learning algorithms: a laboratory for engineering students, 2019.

C075 - Miglianti, F. and Tani, G. and Viviani, M. and Cipollini, F. and Oneto, L., International Symposium on Marine Propulsors (SMP), Data driven models for propeller cavitation noise in model scale, 2019.

C074 - Merello, S. and Picasso, A. and Oneto, L. and Cambria, E., IEEE International Joint Conference on Neural Networks (IJCNN), Ensemble Application of Transfer Learning and Sample Weighting for Stock Market Prediction, 2019.

C073 - Cipollini, F. and Miglianti, F. and Oneto, L. and Tani, G. and Viviani, M., IEEE International Joint Conference on Neural Networks (IJCNN), Hybrid Model for Cavitation Noise Spectra Prediction, 2019.

C072 - Oneto, L. and Donini, M. and Pontil, M., European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), PAC-Bayes and Fairness: Risk and Fairness Bounds on Distribution Dependent Fair Priors., 2019.

C071 - Ducuing, C. and Oneto, L. and Canepa, R., European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), Fairness and Accountability of Machine Learning Models in Railway Market: are Applicable Railway Laws Up to Regulate Them?, 2019.

C070 - Bacciu, D. and Biggio, B. and Lisboa, P. J. G. and Martin, J. D. and Oneto, L. and Vellido, A., European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), Societal Issues in Machine Learning: When Learning from Data is Not Enough., 2019.

C069 - Spigolon, R. and Oneto, L. and Anastasovski, D. and Fabrizio, N. and Swiatek, M. and Canepa, R. and Anguita, D., INNS Big Data and Deep Learning (INNSBDDL), Improving Railway Maintenance Actions with Big Data and Distributed Ledger Technologies., 2019.

C068 - Oneto, L. and Buselli, I. and Sanetti, P. and Canepa, R. and Petralli, S. and Anguita, D., INNS Big Data and Deep Learning (INNSBDDL), Restoration Time Prediction in Large Scale Railway Networks: Big Data and Interpretability., 2019.

C067 - Oneto, L. and Buselli, I. and Luli, A. and Canepa, R. and Petralli, S. and Anguita, D., INNS Big Data and Deep Learning (INNSBDDL), Train Overtaking Prediction in Railway Networks: a Big Data Perspective., 2019.

C066 - Cipollini, F. and Miglianti, F. and Oneto, L. and Tani, G. and Viviani, M. and Anguita, D., INNS Big Data and Deep Learning (INNSBDDL), Cavitation Noise Spectra Prediction with Hybrid Models., 2019.

C065 - Ponta, L. and Puliga, G. and Oneto, L. and Manzini, R., INNS Big Data and Deep Learning (INNSBDDL), Innovation Capability of Firms: A Big Data Approach with patents., 2019.

C064 - Merello, S. and Picasso, A. and Oneto, L. and Cambria, E., INNS Big Data and Deep Learning (INNSBDDL), Predicting future market trends: which is the optimal window?, 2019.

C063 - Schlegel, U. and Jentner, W. and Buchmueller, J. and Cakmak, E. and Castiglia, G. and Canepa, R. and Petralli, S. and Oneto, L. and Keim, D. A. and Anguita, D., INNS Big Data and Deep Learning (INNSBDDL), Visual Analytics for Supporting Conflict Resolution in Large Railway Networks, 2019.

C062 - Oneto, L. and Donini, M. and Elders, A. and Pontil, M., AAAI/ACM Conference on AI, Ethics, and Society (AIES), Taking Advantage of Multitask Learning for Fair Classification, 2018.

C061 - Merello, S. and Picasso, A. and Ma, Y. and Oneto, L. and Cambria, E., IEEE International Conference on Data Mining, International Workshop on Sentiment Elicitation from Natural Text for Information Retrieval and Extraction (ICDM), Investigating Timing and Impact of News on the Stock Market, 2018.

C060 - Donini, M. and Oneto, L. and Ben-David, S. and Shawe-Taylor, J. and Pontil, M., Advances in Neural Information Processing Systems (NIPS), Empirical Risk Minimization Under Fairness Constraints, 2018.

C059 - Picasso, A. and Merello, S. and Ma, Y. and Malandri, L. and Oneto, L. and Cambria, E., IEEE Symposium Series on Computational Intelligence (SSCI, Ensemble of Technical Analysis and Machine Learning for Market Trend Prediction, 2018.

C058 - Coraddu, A. and Kalikatzarakis, M. and Oneto, L. and Meijn, G. J. and Godjevac, M. and Geertsmad, R. D., International Naval Engineering Conference and Exhibition (INEC), Ship diesel engine performance modelling with combined physical and machine learning approach, 2018.

C057 - Lulli, A. and Oneto, L. and Canepa, R. and Petralli, S. and Anguita, D., IEEE International Conference on Data Science and Advanced Analytics (DSAA), Large-Scale Railway Networks Train Movements: a Dynamic, Interpretable, and Robust Hybrid Data Analytics System, 2018.

C056 - Cipollini, F. and Oneto, L. and Coraddu, A., International Symposium On Naval Architecture And Maritime (INT-NAN), A Deep Learning Approach to Marine Propulsion System Maintenance, 2018.

C055 - Cipollini, F. and Oneto, L. and Coraddu, A. and Savio, S. and Anguita, D., INNS International Conference on Big Data and Deep Learning (INNS BDDL), Unintrusive Monitoring of Induction Motors Bearings via Deep Learning on Stator Currents, 2018.

C054 - Oneto, L. and Navarin, N. and Donini, M. and Anguita, D., European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), Emerging Trends in Machine Learning: Beyond Conventional Methods and Data, 2018.

C053 - Oneto, L. and Ridella, S. and Anguita, D., European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), Local Rademacher Complexity Machine, 2018.

C052 - Lulli, A. and Oneto, L. and Anguita, D., IEEE International Conference on Big Data (IEEE BIG DATA), Crack Random Forest for Arbitrary Large Datasets, 2017.

C051 - Oneto, L. and Coraddu, A. and Sanetti, P. and Karpenko, O and Cipollini, F. and Cleophas, T. and Anguita, D., International Conference on Artificial Neural Networks (ICANN), Marine Safety and Data Analytics: Vessel Crash Stop Maneuvering Performance Prediction, 2017.

C050 - Lulli, A. and Oneto, L. and Anguita, D., International Conference on Artificial Neural Networks (ICANN), ReForeSt: Random Forests in Apache Spark, 2017.

C049 - Oneto, L. and Siri, A. and Luria, G. and Anguita, D., European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), Dropout Prediction at University of Genoa: a Privacy Preserving Data Driven Approach, 2017.

C048 - Oneto, L. and Ridella, S. and Anguita, D., European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), Generalization Performances of Randomized Classifiers and Algorithms built on Data Dependent Distributions, 2017.

C047 - Oneto, L. and Navarin, N. and Sperduti, A. and Anguita, D., IEEE International Joint Conference on Neural Networks (IJCNN), Deep Graph Node Kernels: a Convex Approach, 2017.

C046 - Oneto, L. and Fumeo, E. and Clerico, C. and Canepa, R. and Papa, F. and Dambra, C. and Mazzino, N. and Anguita. D., IEEE International Conference on Data Science and Advanced Analytics (DSAA), Advanced Analytics for Train Delay Prediction Systems by Including Exogenous Weather Data, 2016.

C045 - Oneto, L. and Fumeo, E. and Clerico, C. and Canepa, R. and Papa, F. and Dambra, C. and Mazzino, N. and Anguita. D., INNS International Conference on Big Data (INNS BIG DATA), Delay Prediction System for Large-Scale Railway Networks based on Big Data Analytics, 2016.

C044 - Oneto, L. and Coraddu, A. and Anguita, D. and Cleophas, T. and Xepapa, K., International Forum on Research and Technologies for Society and Industry (RTSI), Vessel Monitoring and Design in Industry 4.0: a Data Driven Perspective, 2016.

C043 - Oneto, L. and Navarin, N. and Donini, M. and Aiolli, F. and Anguita, D., European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), Advances in Learning with Kernels: Theory and Practice in a World of growing Constraints, 2016.

C042 - Oneto, L. and Ridella, S. and Anguita, D., European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), Tuning the Distribution Dependent Prior in the PAC-Bayes Framework based on Empirical Data, 2016.

C041 - Orlandi, I. and Oneto, L. and Anguita, D., European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), Random Forests Model Selection, 2016.

C040 - Oneto, L. and Navarin, N. and Donini, M. and Sperduti, A. and Aiolli, F. and Anguita, D., European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), Measuring the Expressivity of Graph Kernels through the Rademacher Complexity, 2016.

C039 - Coraddu, A. and Cleophas, T. and Xepapa, K. and Oneto, L. and Anguita, D., International Conference on Maritime Technology and Engineering (MARTECH), Operational profiles data analytics for ship design improvement, 2016.

C038 - Coraddu, A. and Cleophas, T. and Ivancsics, S. and Oneto, L., International Conference on Computer Applications and Information Technology in the Maritime Industries (COMPIT), Vessel monitoring based on sensors data collection, 2016.

C037 - Vahdat, M. and Oneto, L. and Anguita, D. and Funk, M. and Rauterberg, M., European Conference on Technology Enhanced Learning (EC-TEL), A Learning Analytics Approach to Correlate the Academic Achievements of Students with Interaction Data from an Educational Simulator, 2015.

C036 - Oneto, L. and Orlandi, I. and Anguita, D., IEEE International Conference on Big Data (IEEE BIG DATA), Performance Assessment and Uncertainty Quantification of Predictive Models for Smart Manufacturing Systems, 2015.

C035 - Reyes-Ortiz, J. L. and Oneto, L. and Anguita, D., INNS International Conference on Big Data (INNS BIG DATA), Big Data Analytics in the Cloud: Spark on Hadoop vs MPI/OpenMP on Beowulf, 2015.

C034 - Fumeo, E. and Oneto, L. and Anguita, D., INNS International Conference on Big Data (INNS BIG DATA), Condition Based Maintenance in Railway Transportation Systems Based on Big Data Streaming Analysis, 2015.

C033 - Oneto, L. and Anguita, D., Italian Workshop on Neural Network (WIRN), Learning Hardware Friendly Classifiers through Algorithmic Risk Minimization, 2015.

C032 - Oneto, L. and Ghio, A. and Ridella, S. and Anguita, D., IEEE International Joint Conference on Neural Networks (IJCNN), Shrinkage Learning to Improve SVM with Hints, 2015.

C031 - Oneto, L. and Ghio, A. and Ridella, S. and Anguita, D., IEEE International Joint Conference on Neural Networks (IJCNN), Support Vector Machines and Strictly Positive Definite Kernel: The Regularization Hyperparameter is More Important than the Kernel Hyperparameters, 2015.

C030 - Oneto, L. and Ghio, A. and Ridella, S. and Anguita, D., IEEE International Joint Conference on Neural Networks (IJCNN), Fast Convergence of Extended Rademacher Complexity Bounds, 2015.

C029 - Coraddu, A. and Oneto, L. and Baldi, F. and Anguita, D., IEEE Genova OCEANS'15 MTS, A Ship Efficiency Forecast based on Sensors Data Collection: Improving Numerical Models through Data Analytics, 2015.

C028 - Vahdat, M. and Oneto, L. and Ghio, A. and Anguita, D. and Funk, M. and Rauterberg, M., European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), Advances in learning analytics and educational data mining, 2015.

C027 - Vahdat, M. and Oneto, L. and Ghio, A. and Anguita, D. and Funk, M. and Rauterberg, M., European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), Human Algorithmic Stability and Human Rademacher Complexity, 2015.

C026 - Oneto, L. and Pilarz, B. and Ghio, A. and Anguita, D., European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), Model Selection for Big Data: Algorithmic Stability and Bag of Little Bootstraps on GPUs, 2015.

C025 - Coraddu, A. and Oneto, L. and Ghio, A. and Savio, S. and Figari, M. and Anguita, D., IEEE International Conference on Electrical Systems for Aircraft, Railway, Ship Propulsion and Road Vehicles (ESARS), Machine learning for wear forecasting of naval assets for condition-based maintenance applications, 2015.

C024 - Oneto, L. and Ghio, A. and Ridella, S. and Reyes-Ortiz, J. L. and Anguita, D., IEEE International Conference on Data Mining, International Workshop on High Dimensional Data Mining (ICDM), Out-of-Sample Error Estimation: the Blessing of High Dimensionality, 2014.

C023 - Vahdat, M. and Oneto, L. and Ghio, A. and Donzellini, G. and Anguita, D. and Funk, M. and Rauterberg, M., European Conference on Technology Enhanced Learning (EC-TEL), A Learning Analytics Methodology to Profile Students Behavior and Explore Interactions with Deeds Simulator, 2014.

C022 - Reyes-Ortiz, J. L. and Oneto, L. and Ghio, A. and Anguita, D. and Parra, X., International Conference on Artificial Neural Networks (ICANN), Human Activity Recognition on Smartphones With Awareness of Basic Activities and Postural Transitions, 2014.

C021 - Coraddu, A. and Figari, M. and Ghio, A. and Oneto, L. and Savio, S., International Conference on Computer Applications and Information Technology in the Maritime Industries (COMPIT), A Sustainability Analytics Matlab Tool to Predict Ship Energy Consumption, 2014.

C020 - Anguita, D. and Ghio, A. and Oneto, L. and Ridella, S., IEEE International Joint Conference on Neural Networks (IJCNN), Smartphone Battery Saving by Bit-Based Hypothesis Spaces and Local Rademacher Complexities, 2014.

C019 - Ghio, A. and Oneto, L., European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), Byte The Bullet: Learning on Real-World Computing Architectures, 2014.

C018 - Anguita, D. and Ghio, A. and Oneto, L. and Ridella, S., European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), Learning with Few Bits on Small-Scale Devices: from Regularization to Energy Efficiency, 2014.

C017 - Anguita, D. and Ghio, A. and Oneto, L. and Parra, X. and Reyes-Ortiz, J. L., International Conference on Artificial Neural Networks (ICANN), Training Computationally Efficient Smartphone-Based Human Activity Recognition Models, 2013.

C016 - Anguita, D. and Ghio, A. and Oneto, L. and Reyes-Ortiz, J. L. and Ridella, S., International Conference on Artificial Neural Networks (ICANN), A Novel Procedure for Training L1-L2 Support Vector Machine Classifiers, 2013.

C015 - Anguita, D. and Ghio, A. and Lawal, I. A. and Oneto, L., International Workshop on Advances in Regularization, Optimization, Kernel Methods and Support Vector Machines: theory and applications (ROKS), A Heuristic Approach to Model Selection for Online Support Vector Machines, 2013.

C014 - Anguita, D. and Ghio, A. and Oneto, L. and Ridella, S., IEEE International Joint Conference on Neural Networks (IJCNN), Some Results About the Vapnik-Chervonenkis Entropy and the Rademacher Complexity, 2013.

C013 - Anguita, D. and Ghio, A. and Oneto, L. and Ridella, S., IEEE International Joint Conference on Neural Networks (IJCNN), A Support Vector Machine Classifier from a Bit-Constrained, Sparse and Localized Hypothesis Space, 2013.

C012 - Anguita, D. and Ghio, A. and Oneto, L. and Ridella, S., European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), A Learning Machine with a Bit-Based Hypothesis Space, 2013.

C011 - Anguita, D. and Ghio, A. and Oneto, L. and Parra, X. and Reyes-Ortiz, J. L., European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), A Public Domain Dataset for Human Activity Recognition using Smartphones, 2013.

C010 - Anguita, D. and Ghio, A. and Oneto, L. and Parra, X. and Reyes-Ortiz, J. L., International Workshop on Ambient Assisted Living (IWAAL), Human Activity Recognition on Smartphones using a Multiclass Hardware-Friendly Support Vector Machine, 2012.

C009 - Anguita, D. and Ghio, A. and Oneto, L. and Ridella, S. and Schatten, C., International Conference on Artificial Neural Networks (ICANN), Nested Sequential Minimal Optimization for Support Vector Machine, 2012.

C008 - Anguita, D. and Ghio, A. and Oneto, L. and Ridella, S., International Conference on Artificial Neural Networks (ICANN), Rademacher Complexity and Structural Risk Minimization: an Application to Human Gene Expression Datasets, 2012.

C007 - Anguita, D. and Ghelardoni, L. and Ghio, A. and Oneto, L. and Ridella, S., European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), The 'K' in K-fold Cross Validation, 2012.

C006 - Anguita, D. and Ghio, A. and Oneto, L. and Ridella, S., European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), Structural Risk Minimization and Rademacher Complexity for Regression, 2012.

C005 - Anguita, D. and Ghio, A. and Oneto, L. and Ridella, S., Advances in Neural Information Processing Systems (NIPS), The Impact of Unlabeled Patterns in Rademacher Complexity Theory for Kernel Classifiers, 2011.

C004 - Anguita, D. and Ghio, A. and Oneto, L. and Ridella, S., IEEE International Joint Conference on Neural Networks (IJCNN), In-sample Model Selection for Support Vector Machines, 2011.

C003 - Anguita, D. and Ghio, A. and Oneto, L. and Ridella, S., IEEE International Joint Conference on Neural Networks (IJCNN), Selecting the Hypothesis Space for Improving the Generalization Ability of Support Vector Machines, 2011.

C002 - Anguita, D. and Ghio, A. and Oneto, L. and Ridella, S., European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), Maximal Discrepancy vs. Rademacher Complexity for Error Estimation, 2011.

C001 - Anguita, D. and Ghio, A. and Greco, N. and Oneto, L. and Ridella, S., IEEE International Joint Conference on Neural Networks (IJCNN), Model selection for support vector machines: Advantages and disadvantages of the machine learning theory, 2010.