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2020 – today
- 2024
[j66]Davide Ilardi
, Miltiadis Kalikatzarakis, Luca Oneto, Maurizio Collu, Andrea Coraddu:
Computationally Aware Surrogate Models for the Hydrodynamic Response Characterization of Floating Spar-Type Offshore Wind Turbine. IEEE Access 12: 6494-6517 (2024)- [j65]Jake M. Walker, Andrea Coraddu, Luca Oneto:
Data-Driven Models for Yacht Hull Resistance Optimization: Exploring Geometric Parameters Beyond the Boundaries of the Delft Systematic Yacht Hull Series. IEEE Access 12: 76102-76120 (2024) - [j64]Danilo Franco, Vincenzo Stefano D'Amato, Luca Pasa, Nicolò Navarin, Luca Oneto:
Fair graph representation learning: Empowering NIFTY via Biased Edge Dropout and Fair Attribute Preprocessing. Neurocomputing 563: 126948 (2024) - [j63]Nicolò Navarin, Dounia Mulders, Luca Oneto:
Advances in artificial neural networks, machine learning and computational intelligence. Neurocomputing 571: 127098 (2024) - [j62]Luca Oneto, Sandro Ridella, Davide Anguita:
Towards algorithms and models that we can trust: A theoretical perspective. Neurocomputing 592: 127798 (2024) - [j61]Giovanni Donghi, Luca Pasa, Luca Oneto, Claudio Gallicchio, Alessio Micheli, Davide Anguita, Alessandro Sperduti, Nicolò Navarin:
Investigating over-parameterized randomized graph networks. Neurocomputing 606: 128281 (2024) - [i8]Daniele Angioni, Luca Demetrio, Maura Pintor, Luca Oneto, Davide Anguita, Battista Biggio, Fabio Roli:
Robustness-Congruent Adversarial Training for Secure Machine Learning Model Updates. CoRR abs/2402.17390 (2024) - [i7]Zhang Chen, Luca Demetrio, Srishti Gupta, Xiaoyi Feng, Zhaoqiang Xia, Antonio Emanuele Cinà, Maura Pintor, Luca Oneto, Ambra Demontis, Battista Biggio, Fabio Roli:
Over-parameterization and Adversarial Robustness in Neural Networks: An Overview and Empirical Analysis. CoRR abs/2406.10090 (2024) - 2023
- [b1]Giuliano Donzellini, Luca Oneto, Domenico Ponta, Davide Anguita:
Introduzione al Progetto di Sistemi Digitali, 2a Edition. Springer 2023, ISBN 978-88-470-4025-0, pp. 1-572 - [j60]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, Cristina Becchio, Benoît G. Bardy, Nadia Bianchi-Berthouze:
Human Movement Datasets: An Interdisciplinary Scoping Review. ACM Comput. Surv. 55(6): 126:1-126:29 (2023) - [j59]Miltiadis Kalikatzarakis, Andrea Coraddu, Mehmet Atlar, Stefano Gaggero, Giorgio Tani, Luca Oneto:
Physically plausible propeller noise prediction via recursive corrections leveraging prior knowledge and experimental data. Eng. Appl. Artif. Intell. 118: 105660 (2023) - [j58]Luca Oneto, Sandro Ridella, Davide Anguita:
Do we really need a new theory to understand over-parameterization? Neurocomputing 543: 126227 (2023) - [j57]Alvise De Biasio, Merylin Monaro, Luca Oneto, Lamberto Ballan, Nicolò Navarin:
On the problem of recommendation for sensitive users and influential items: Simultaneously maintaining interest and diversity. Knowl. Based Syst. 275: 110699 (2023) - [c106]Daniele Giampaoli, Francesca Cipollini, Denise Maffione, Luca Oneto:
Short-term Forecast and Long-term Simulation for Accurate Energy Consumption Prediction. DSAA 2023: 1-4 - [c105]Andrea Ceni, Davide Bacciu, Valerio De Caro, Claudio Gallicchio, Luca Oneto:
Improving Fairness via Intrinsic Plasticity in Echo State Networks. ESANN 2023 - [c104]Danilo Franco, Luca Oneto, Davide Anguita:
Mitigating Robustness Bias: Theoretical Results and Empirical Evidences. ESANN 2023 - [c103]Nicolò Navarin, Luca Pasa, Luca Oneto, Alessandro Sperduti:
An Empirical Study of Over-Parameterized Neural Models based on Graph Random Features. ESANN 2023 - [c102]Luca Oneto, Sandro Ridella, Davide Anguita:
Towards Randomized Algorithms and Models that We Can Trust: a Theoretical Perspective. ESANN 2023 - [c101]Danilo Franco, Luca Oneto, Davide Anguita:
Fair Empirical Risk Minimization Revised. IWANN (1) 2023: 29-42 - [c100]Giovanni Graziano, Daniele Ucci, Federica Bisio, Luca Oneto:
PhishVision: A Deep Learning Based Visual Brand Impersonation Detector for Identifying Phishing Attacks. OL2A (1) 2023: 123-134 - [c99]Guido Parodi, Luca Oneto, Giulio Ferro, Stefano Zampini, Michela Robba, Davide Anguita, Andrea Coraddu:
Physics Informed Data Driven Techniques for Power Flow Analysis. SSCI 2023: 33-40 - 2022
- [j56]Luca Oneto, Kerstin Bunte, Nicolò Navarin:
Advances in artificial neural networks, machine learning and computational intelligence. Neurocomputing 470: 300-303 (2022) - [j55]Danilo Franco, Nicolò Navarin, Michele Donini, Davide Anguita, Luca Oneto:
Deep fair models for complex data: Graphs labeling and explainable face recognition. Neurocomputing 470: 318-334 (2022) - [j54]Luca Oneto, Nicolò Navarin, Battista Biggio, Federico Errica, Alessio Micheli, Franco Scarselli, Monica Bianchini, Luca Demetrio, Pietro Bongini, Armando Tacchella, Alessandro Sperduti:
Towards learning trustworthily, automatically, and with guarantees on graphs: An overview. Neurocomputing 493: 217-243 (2022) - [j53]Luca Oneto, Sandro Ridella, Davide Anguita:
The benefits of adversarial defense in generalization. Neurocomputing 505: 125-141 (2022) - [j52]Luca Oneto, Nicolò Navarin, Frank-Michael Schleif:
Advances in artificial neural networks, machine learning and computational intelligence. Neurocomputing 507: 311-314 (2022) - [j51]Davide Chicco, Luca Oneto, Erica Tavazzi:
Eleven quick tips for data cleaning and feature engineering. PLoS Comput. Biol. 18(12): 1010718 (2022) - [j50]Miltiadis Kalikatzarakis, Andrea Coraddu, Luca Oneto, Davide Anguita:
Optimizing Fuel Consumption in Thrust Allocation for Marine Dynamic Positioning Systems. IEEE Trans Autom. Sci. Eng. 19(1): 122-142 (2022) - [j49]Linda Ponta, Gloria Puliga, Luca Oneto, Raffaella Manzini:
Identifying the Determinants of Innovation Capability With Machine Learning and Patents. IEEE Trans. Engineering Management 69(5): 2144-2154 (2022) - [c98]Marco Demutti, Vincenzo Stefano D'Amato, Carmine Tommaso Recchiuto, Luca Oneto, Antonio Sgorbissa:
A Cloud Architecture for Emotion Recognition Based on the Appraisal Theory (short paper). AIRO@AI*IA 2022: 19-24 - [c97]Ariel Gjaci, Luca Oneto, Carmine Tommaso Recchiuto, Antonio Sgorbissa:
Culture Awareness in Intelligent Systems (short paper). AIRO@AI*IA 2022: 25-30 - [c96]Federico Caldart, Luca Pasa, Luca Oneto, Alessandro Sperduti, Nicolò Navarin:
Biased Edge Dropout in NIFTY for Fair Graph Representation Learning. ESANN 2022 - [c95]Luca Oneto, Simone Minisi, Andrea Garrone, Renzo Canepa, Carlo Dambra, Davide Anguita:
Simple Non Regressive Informed Machine Learning Model for Predictive Maintenance of Railway Critical Assets. ESANN 2022 - [c94]Luca Oneto, Sandro Ridella, Davide Anguita:
Do We Really Need a New Theory to Understand the Double-Descent? ESANN 2022 - [c93]Vincenzo Stefano D'Amato, Luca Oneto, Antonio Camurri, Davide Anguita:
The Importance of Multiple Temporal Scales in Motion Recognition: when Shallow Model can Support Deep Multi Scale Models. IJCNN 2022: 1-10 - [c92]Vincenzo Stefano D'Amato, Luca Oneto, Antonio Camurri, Davide Anguita, Zinat Zarandi, Luciano Fadiga, Alessandro D'Ausilio, Thierry Pozzo:
The Importance of Multiple Temporal Scales in Motion Recognition: from Shallow to Deep Multi Scale Models. IJCNN 2022: 1-9 - [c91]Carmine Dodaro, Davide Ilardi, Luca Oneto, Francesco Ricca:
Deep Learning for the Generation of Heuristics in Answer Set Programming: A Case Study of Graph Coloring. LPNMR 2022: 145-158 - [c90]Marco Demutti, Vincenzo Stefano D'Amato, Carmine Recchiuto, Luca Oneto, Antonio Sgorbissa:
Assessing Emotions in Human-Robot Interaction Based on the Appraisal Theory. RO-MAN 2022: 1435-1442 - [c89]Andrea Garrone, Simone Minisi, Luca Oneto, Carlo Dambra, Marco Borinato, Paolo Sanetti, Giulia Vignola, Federico Papa, Nadia Mazzino, Davide Anguita:
Simple Non Regressive Informed Machine Learning Model for Prescriptive Maintenance of Track Circuits in a Subway Environment. SYSINT 2022: 74-83 - [c88]Irene Buselli, Luca Oneto, Carlo Dambra, Christian Verdonk Gallego, Miguel Garcia Martinez:
Data-Driven Methods for Aviation Safety: From Data to Knowledge. SYSINT 2022: 126-136 - 2021
- [j48]Davide Chicco, Christopher A. Lovejoy, Luca Oneto:
A Machine Learning Analysis of Health Records of Patients With Chronic Kidney Disease at Risk of Cardiovascular Disease. IEEE Access 9: 165132-165144 (2021) - [j47]Davide Chicco, Luca Oneto:
Data analytics and clinical feature ranking of medical records of patients with sepsis. BioData Min. 14(1): 12 (2021) - [j46]Andrea Coraddu, Luca Oneto, Davide Ilardi, Sokratis Stoumpos, Gerasimos Theotokatos:
Marine dual fuel engines monitoring in the wild through weakly supervised data analytics. Eng. Appl. Artif. Intell. 100: 104179 (2021) - [j45]Luca Oneto, Sandro Ridella:
Distribution-Dependent Weighted Union Bound. Entropy 23(1): 101 (2021) - [j44]Danilo Franco, Luca Oneto, Nicolò Navarin, Davide Anguita:
Toward Learning Trustworthily from Data Combining Privacy, Fairness, and Explainability: An Application to Face Recognition. Entropy 23(8): 1047 (2021) - [j43]Davide Chicco, Luca Oneto:
Computational intelligence identifies alkaline phosphatase (ALP), alpha-fetoprotein (AFP), and hemoglobin levels as most predictive survival factors for hepatocellular carcinoma. Health Informatics J. 27(1): 146045822098420 (2021) - [j42]Davide Chicco, Luca Oneto:
An Enhanced Random Forests Approach to Predict Heart Failure From Small Imbalanced Gene Expression Data. IEEE ACM Trans. Comput. Biol. Bioinform. 18(6): 2759-2765 (2021) - [c87]Vincenzo Stefano D'Amato, Luca Oneto, Antonio Camurri, Davide Anguita:
Keep it Simple: Handcrafting Feature and Tuning Random Forests and XGBoost to face the Affective Movement Recognition Challenge 2021. ACII (Workshops and Demos) 2021: 1-7 - [c86]Matteo Cardellini, Marco Maratea, Mauro Vallati, Gianluca Boleto, Luca Oneto:
In-Station Train Dispatching: A PDDL+ Planning Approach. ICAPS 2021: 450-458 - [c85]Gianluca Boleto, Luca Oneto, Matteo Cardellini, Marco Maratea, Mauro Vallati, Renzo Canepa, Davide Anguita:
In-Station Train Movements Prediction: from Shallow to Deep Multi Scale Models. ESANN 2021 - [c84]Luca Oneto, Nicolò Navarin, Battista Biggio, Federico Errica, Alessio Micheli, Franco Scarselli, Monica Bianchini, Alessandro Sperduti:
Complex Data: Learning Trustworthily, Automatically, and with Guarantees. ESANN 2021 - [c83]Luca Oneto, Sandro Ridella, Davide Anguita:
The Benefits of Adversarial Defence in Generalisation. ESANN 2021 - [c82]Matteo Cardellini, Marco Maratea, Mauro Vallati, Gianluca Boleto, Luca Oneto:
An Efficient Hybrid Planning Framework for In-Station Train Dispatching. ICCS (1) 2021: 168-182 - [c81]Danilo Franco, Luca Oneto, Nicolò Navarin, Davide Anguita:
Learn and Visually Explain Deep Fair Models: an Application to Face Recognition. IJCNN 2021: 1-10 - [c80]Vincenzo Stefano D'Amato, Erica Volta, Luca Oneto, Gualtiero Volpe, Antonio Camurri, Davide Anguita:
Accuracy and Intrusiveness in Data-Driven Violin Players Skill Levels Prediction: MOCAP Against MYO Against KINECT. IWANN (2) 2021: 367-379 - [c79]Matteo Cardellini, Marco Maratea, Mauro Vallati, Gianluca Boleto, Luca Oneto:
A Planning-based Approach for In-Station Train Dispatching. SOCS 2021: 156-158 - 2020
- [j41]Vincenzo Stefano D'Amato, Erica Volta, Luca Oneto, Gualtiero Volpe, Antonio Camurri, Davide Anguita:
Understanding Violin Players' Skill Level Based on Motion Capture: a Data-Driven Perspective. Cogn. Comput. 12(6): 1356-1369 (2020) - [j40]Luca Oneto:
Learning fair models and representations. Intelligenza Artificiale 14(1): 151-178 (2020) - [j39]Luca Oneto, Irene Buselli, Alessandro Lulli, Renzo Canepa, Simone Petralli, Davide Anguita:
A dynamic, interpretable, and robust hybrid data analytics system for train movements in large-scale railway networks. Int. J. Data Sci. Anal. 9(1): 95-111 (2020) - [j38]Luca Oneto, Kerstin Bunte, Alessandro Sperduti:
Advances in artificial neural networks, machine learning and computational intelligence. Neurocomputing 416: 172-176 (2020) - [j37]Luca Oneto, Michele Donini, Massimiliano Pontil, John Shawe-Taylor:
Randomized learning and generalization of fair and private classifiers: From PAC-Bayes to stability and differential privacy. Neurocomputing 416: 231-243 (2020) - [j36]Simone Aonzo, Alessio Merlo, Mauro Migliardi, Luca Oneto, Francesco Palmieri:
Low-Resource Footprint, Data-Driven Malware Detection on Android. IEEE Trans. Sustain. Comput. 5(2): 213-222 (2020) - [c78]Luca Oneto, Michele Donini, Massimiliano Pontil, Andreas Maurer:
Learning Fair and Transferable Representations with Theoretical Guarantees. DSAA 2020: 30-39 - [c77]Luca Oneto, Nicolò Navarin, Michele Donini:
Learning Deep Fair Graph Neural Networks. ESANN 2020: 31-36 - [c76]Luca Oneto, Sandro Ridella, Davide Anguita:
Improving the Union Bound: a Distribution Dependent Approach. ESANN 2020: 423-428 - [c75]Nicolò Navarin, Matteo Cambiaso, Andrea Burattin, Fabrizio Maria Maggi, Luca Oneto, Alessandro Sperduti:
Towards Online Discovery of Data-Aware Declarative Process Models from Event Streams. IJCNN 2020: 1-8 - [c74]Luca Oneto, Francesca Cipollini, Leonardo Miglianti, Giorgio Tani, Stefano Gaggero, Michele Viviani, Andrea Coraddu:
Deep Learning for Cavitating Marine Propeller Noise Prediction at Design Stage. IJCNN 2020: 1-10 - [c73]Luca Oneto, Michele Donini, Massimiliano Pontil:
General Fair Empirical Risk Minimization. IJCNN 2020: 1-8 - [c72]Evgenii Chzhen, Christophe Denis, Mohamed Hebiri, Luca Oneto, Massimiliano Pontil:
Fair regression with Wasserstein barycenters. NeurIPS 2020 - [c71]Evgenii Chzhen, Christophe Denis, Mohamed Hebiri, Luca Oneto, Massimiliano Pontil:
Fair regression via plug-in estimator and recalibration with statistical guarantees. NeurIPS 2020 - [c70]Luca Oneto, Michele Donini, Giulia Luise, Carlo Ciliberto, Andreas Maurer, Massimiliano Pontil:
Exploiting MMD and Sinkhorn Divergences for Fair and Transferable Representation Learning. NeurIPS 2020 - [e2]Luca Oneto, Nicolò Navarin, Alessandro Sperduti, Davide Anguita:
Recent Advances in Big Data and Deep Learning, Proceedings of the INNS Big Data and Deep Learning Conference INNSBDDL 2019, held at Sestri Levante, Genova, Italy 16-18 April 2019. Springer 2020, ISBN 978-3-030-16840-7 [contents] - [e1]Luca Oneto, Nicolò Navarin, Alessandro Sperduti, Davide Anguita:
Recent Trends in Learning From Data - Tutorials from the INNS Big Data and Deep Learning Conference (INNSBDDL 2019). Studies in Computational Intelligence 896, Springer 2020, ISBN 978-3-030-43882-1 [contents] - [i6]Evgenii Chzhen, Christophe Denis, Mohamed Hebiri, Luca Oneto, Massimiliano Pontil:
Fair Regression with Wasserstein Barycenters. CoRR abs/2006.07286 (2020) - [i5]Luca Oneto, Silvia Chiappa:
Fairness in Machine Learning. CoRR abs/2012.15816 (2020)
2010 – 2019
- 2019
- [j35]Alessandro Lulli, Luca Oneto, Davide Anguita:
Mining Big Data with Random Forests. Cogn. Comput. 11(2): 294-316 (2019) - [j34]Andrea Picasso Ratto, Simone Merello, Yukun Ma, Luca Oneto, Erik Cambria:
Technical analysis and sentiment embeddings for market trend prediction. Expert Syst. Appl. 135: 60-70 (2019) - [j33]Luca Oneto, Kerstin Bunte, Frank-Michael Schleif:
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). Neurocomputing 342: 1-5 (2019) - [j32]Luca Oneto, Sandro Ridella, Davide Anguita:
Local Rademacher Complexity Machine. Neurocomputing 342: 24-32 (2019) - [j31]Alessio Carrega, Francesca Cipollini, Luca Oneto:
Simple continuous optimal regions of the space of data. Neurocomputing 349: 91-104 (2019) - [c69]Luca Oneto, Michele Donini, Amon Elders, Massimiliano Pontil:
Taking Advantage of Multitask Learning for Fair Classification. AIES 2019: 227-237 - [c68]Davide Bacciu, Battista Biggio, Paulo Lisboa, José D. Martín, Luca Oneto, Alfredo Vellido:
Societal Issues in Machine Learning: When Learning from Data is Not Enough. ESANN 2019 - [c67]Charlotte Ducuing, Luca Oneto, Renzo Canepa:
Fairness and Accountability of Machine Learning Models in Railway Market: are Applicable Railway Laws Up to Regulate Them? ESANN 2019 - [c66]Luca Oneto, Michele Donini, Massimiliano Pontil:
PAC-Bayes and Fairness: Risk and Fairness Bounds on Distribution Dependent Fair Priors. ESANN 2019 - [c65]Francesca Cipollini, Fabiana Miglianti, Luca Oneto, Giorgio Tani, Michele Viviani:
Hybrid Model for Cavitation Noise Spectra Prediction. IJCNN 2019: 1-8 - [c64]Simone Merello, Andrea Picasso Ratto, Luca Oneto, Erik Cambria:
Ensemble Application of Transfer Learning and Sample Weighting for Stock Market Prediction. IJCNN 2019: 1-8 - [c63]Luca Oneto, Nicolò Navarin, Alessandro Sperduti, Davide Anguita:
Introduction. INNSBDDL (Tutorials) 2019: 1-4 - [c62]Roberto Spigolon, Luca Oneto, Dimitar Anastasovski, Nadia Fabrizio, Marie Swiatek, Renzo Canepa, Davide Anguita:
Improving Railway Maintenance Actions with Big Data and Distributed Ledger Technologies. INNSBDDL 2019: 120-125 - [c61]Luca Oneto, Irene Buselli, Paolo Sanetti, Renzo Canepa, Simone Petralli, Davide Anguita:
Restoration Time Prediction in Large Scale Railway Networks: Big Data and Interpretability. INNSBDDL 2019: 136-141 - [c60]Luca Oneto, Irene Buselli, Alessandro Lulli, Renzo Canepa, Simone Petralli, Davide Anguita:
Train Overtaking Prediction in Railway Networks: A Big Data Perspective. INNSBDDL 2019: 142-151 - [c59]Francesca Cipollini, Fabiana Miglianti, Luca Oneto, Giorgio Tani, Michele Viviani, Davide Anguita:
Cavitation Noise Spectra Prediction with Hybrid Models. INNSBDDL 2019: 152-157 - [c58]Luca Oneto, Silvia Chiappa:
Fairness in Machine Learning. INNSBDDL (Tutorials) 2019: 155-196 - [c57]Linda Ponta, Gloria Puliga, Luca Oneto, Raffaella Manzini:
Innovation Capability of Firms: A Big Data Approach with Patents. INNSBDDL 2019: 169-179 - [c56]Simone Merello, Andrea Picasso Ratto, Luca Oneto, Erik Cambria:
Predicting Future Market Trends: Which Is the Optimal Window? INNSBDDL 2019: 180-185 - [c55]Udo Schlegel, Wolfgang Jentner, Juri Buchmüller, Eren Cakmak, Giuliano Castiglia, Renzo Canepa, Simone Petralli, Luca Oneto, Daniel A. Keim, Davide Anguita:
Visual Analytics for Supporting Conflict Resolution in Large Railway Networks. INNSBDDL 2019: 206-215 - [c54]Alice Consilvio, Paolo Sanetti, Davide Anguita, Carlo Crovetto, Carlo Dambra, Luca Oneto, Federico Papa, Nicola Sacco:
Prescriptive Maintenance of Railway Infrastructure: From Data Analytics to Decision Support. MT-ITS 2019: 1-10 - [c53]Evgenii Chzhen, Christophe Denis, Mohamed Hebiri, Luca Oneto, Massimiliano Pontil:
Leveraging Labeled and Unlabeled Data for Consistent Fair Binary Classification. NeurIPS 2019: 12739-12750 - [i4]Luca Oneto, Michele Donini, Massimiliano Pontil:
General Fair Empirical Risk Minimization. CoRR abs/1901.10080 (2019) - [i3]Luca Oneto, Michele Donini, Andreas Maurer, Massimiliano Pontil:
Learning Fair and Transferable Representations. CoRR abs/1906.10673 (2019) - 2018
- [j30]Luca Oneto, Emanuele Fumeo, Giorgio Clerico, Renzo Canepa, Federico Papa, Carlo Dambra, Nadia Mazzino, Davide Anguita:
Train Delay Prediction Systems: A Big Data Analytics Perspective. Big Data Res. 11: 54-64 (2018) - [j29]Fabio Aiolli, Michael Biehl, Luca Oneto:
Advances in artificial neural networks, machine learning and computational intelligence. Neurocomputing 298: 1-3 (2018) - [j28]Luca Oneto, Francesca Cipollini, Sandro Ridella, Davide Anguita:
Randomized learning: Generalization performance of old and new theoretically grounded algorithms. Neurocomputing 298: 21-33 (2018) - [j27]Luca Oneto, Nicolò Navarin, Alessandro Sperduti, Davide Anguita:
Multilayer Graph Node Kernels: Stacking While Maintaining Convexity. Neural Process. Lett. 48(2): 649-667 (2018) - [j26]Francesca Cipollini, Luca Oneto, Andrea Coraddu, Alan John Murphy, Davide Anguita:
Condition-based maintenance of naval propulsion systems: Data analysis with minimal feedback. Reliab. Eng. Syst. Saf. 177: 12-23 (2018) - [j25]Luca Oneto, Federica Laureri, Michela Robba, Federico Delfino, Davide Anguita:
Data-Driven Photovoltaic Power Production Nowcasting and Forecasting for Polygeneration Microgrids. IEEE Syst. J. 12(3): 2842-2853 (2018) - [j24]Luca Oneto, Nicolò Navarin, Michele Donini, Sandro Ridella, Alessandro Sperduti, Fabio Aiolli, Davide Anguita:
Learning With Kernels: A Local Rademacher Complexity-Based Analysis With Application to Graph Kernels. IEEE Trans. Neural Networks Learn. Syst. 29(10): 4660-4671 (2018) - [j23]Luca Oneto:
Model selection and error estimation without the agonizing pain. WIREs Data Mining Knowl. Discov. 8(4) (2018) - [c52]Alessandro Lulli, Luca Oneto, Renzo Canepa, Simone Petralli, Davide Anguita:
Large-Scale Railway Networks Train Movements: A Dynamic, Interpretable, and Robust Hybrid Data Analytics System. DSAA 2018: 371-380 - [c51]Luca Oneto, Nicolò Navarin, Michele Donini, Davide Anguita:
Emerging trends in machine learning: beyond conventional methods and data. ESANN 2018 - [c50]Luca Oneto, Sandro Ridella, Davide Anguita:
Local Rademacher Complexity Machine. ESANN 2018 - [c49]Simone Merello, Andrea Picasso Ratto, Yukun Ma, Luca Oneto, Erik Cambria:
Investigating Timing and Impact of News on the Stock Market. ICDM Workshops 2018: 1348-1354 - [c48]Francesca Cipollini, Luca Oneto, Andrea Coraddu, Stefano Savio, Davide Anguita:
Unintrusive Monitoring of Induction Motors Bearings via Deep Learning on Stator Currents. INNS Conference on Big Data 2018: 42-51 - [c47]Michele Donini, Luca Oneto, Shai Ben-David, John Shawe-Taylor, Massimiliano Pontil:
Empirical Risk Minimization Under Fairness Constraints. NeurIPS 2018: 2796-2806 - [c46]Andrea Picasso Ratto, Simone Merello, Luca Oneto, Yukun Ma, Lorenzo Malandri, Erik Cambria:
Ensemble of Technical Analysis and Machine Learning for Market Trend Prediction. SSCI 2018: 2090-2096 - [i2]Michele Donini, Luca Oneto, Shai Ben-David, John Shawe-Taylor, Massimiliano Pontil:
Empirical Risk Minimization under Fairness Constraints. CoRR abs/1802.08626 (2018) - [i1]Luca Oneto, Michele Donini, Amon Elders, Massimiliano Pontil:
Taking Advantage of Multitask Learning for Fair Classification. CoRR abs/1810.08683 (2018) - 2017
- [j22]Luca Oneto, Federica Bisio, Erik Cambria, Davide Anguita:
Semi-supervised Learning for Affective Common-Sense Reasoning. Cogn. Comput. 9(1): 18-42 (2017) - [j21]Luca Oneto, Federica Bisio, Erik Cambria, Davide Anguita:
SLT-Based ELM for Big Social Data Analysis. Cogn. Comput. 9(2): 259-274 (2017) - [j20]Luca Oneto, Nicolò Navarin, Michele Donini, Alessandro Sperduti, Fabio Aiolli, Davide Anguita:
Measuring the expressivity of graph kernels through Statistical Learning Theory. Neurocomputing 268: 4-16 (2017) - [j19]Luca Oneto, Sandro Ridella, Davide Anguita:
Differential privacy and generalization: Sharper bounds with applications. Pattern Recognit. Lett. 89: 31-38 (2017) - [j18]Luca Oneto, Emanuele Fumeo, Giorgio Clerico, Renzo Canepa, Federico Papa, Carlo Dambra, Nadia Mazzino, Davide Anguita:
Dynamic Delay Predictions for Large-Scale Railway Networks: Deep and Shallow Extreme Learning Machines Tuned via Thresholdout. IEEE Trans. Syst. Man Cybern. Syst. 47(10): 2754-2767 (2017) - [c45]Alessandro Lulli, Luca Oneto, Davide Anguita:
Crack random forest for arbitrary large datasets. IEEE BigData 2017: 706-715 - [c44]Luca Oneto, Sandro Ridella, Davide Anguita:
Generalization Performances of Randomized Classifiers and Algorithms built on Data Dependent Distributions. ESANN 2017 - [c43]Luca Oneto, Anna Siri, Gianvittorio Luria, Davide Anguita:
Dropout Prediction at University of Genoa: a Privacy Preserving Data Driven Approach. ESANN 2017 - [c42]Alessandro Lulli, Luca Oneto, Davide Anguita:
ReForeSt: Random Forests in Apache Spark. ICANN (2) 2017: 331-339 - [c41]Luca Oneto, Andrea Coraddu, Paolo Sanetti, Olena Karpenko, Francesca Cipollini, Toine Cleophas, Davide Anguita:
Marine Safety and Data Analytics: Vessel Crash Stop Maneuvering Performance Prediction. ICANN (2) 2017: 385-393 - [c40]Luca Oneto, Nicolò Navarin, Alessandro Sperduti, Davide Anguita:
Deep graph node kernels: A convex approach. IJCNN 2017: 316-323 - 2016
- [j17]Luca Oneto, Federica Bisio, Erik Cambria, Davide Anguita:
Statistical Learning Theory and ELM for Big Social Data Analysis. IEEE Comput. Intell. Mag. 11(3): 45-55 (2016) - [j16]Jorge Luis Reyes-Ortiz, Luca Oneto, Albert Samà, Xavier Parra, Davide Anguita:
Transition-Aware Human Activity Recognition Using Smartphones. Neurocomputing 171: 754-767 (2016) - [j15]Mehrnoosh Vahdat, Luca Oneto, Davide Anguita, Mathias Funk, Matthias Rauterberg:
Can machine learning explain human learning? Neurocomputing 192: 14-28 (2016) - [j14]Luca Oneto, Sandro Ridella, Davide Anguita:
Tikhonov, Ivanov and Morozov regularization for support vector machine learning. Mach. Learn. 103(1): 103-136 (2016) - [j13]Luca Oneto, Davide Anguita, Sandro Ridella:
A local Vapnik-Chervonenkis complexity. Neural Networks 82: 62-75 (2016) - [j12]Luca Oneto, Alessandro Ghio, Sandro Ridella, Davide Anguita:
Global Rademacher Complexity Bounds: From Slow to Fast Convergence Rates. Neural Process. Lett. 43(2): 567-602 (2016) - [j11]Luca Oneto, Davide Anguita, Sandro Ridella:
PAC-bayesian analysis of distribution dependent priors: Tighter risk bounds and stability analysis. Pattern Recognit. Lett. 80: 200-207 (2016) - [j10]Luca Oneto, Sandro Ridella, Davide Anguita:
Learning Hardware-Friendly Classifiers Through Algorithmic Stability. ACM Trans. Embed. Comput. Syst. 15(2): 23:1-23:29 (2016) - [c39]Luca Oneto, Emanuele Fumeo, Giorgio Clerico, Renzo Canepa, Federico Papa, Carlo Dambra, Nadia Mazzino, Davide Anguita:
Advanced Analytics for Train Delay Prediction Systems by Including Exogenous Weather Data. DSAA 2016: 458-467 - [c38]Luca Oneto, Nicolò Navarin, Michele Donini, Fabio Aiolli, Davide Anguita:
Advances in Learning with Kernels: Theory and Practice in a World of growing Constraints. ESANN 2016 - [c37]Luca Oneto, Nicolò Navarin, Michele Donini, Alessandro Sperduti, Fabio Aiolli, Davide Anguita:
Measuring the Expressivity of Graph Kernels through the Rademacher Complexity. ESANN 2016 - [c36]Luca Oneto, Sandro Ridella, Davide Anguita:
Tuning the Distribution Dependent Prior in the PAC-Bayes Framework based on Empirical Data. ESANN 2016 - [c35]Ilenia Orlandi, Luca Oneto, Davide Anguita:
Random Forests Model Selection. ESANN 2016 - [c34]Luca Oneto, Emanuele Fumeo, Giorgio Clerico, Renzo Canepa, Federico Papa, Carlo Dambra, Nadia Mazzino, Davide Anguita:
Delay Prediction System for Large-Scale Railway Networks Based on Big Data Analytics. INNS Conference on Big Data 2016: 139-150 - [c33]Luca Oneto, Davide Anguita, Andrea Coraddu, Toine Cleophas, Katerina Xepapa:
Vessel monitoring and design in industry 4.0: A data driven perspective. RTSI 2016: 1-6 - [p1]Luca Oneto, Davide Anguita:
Learning Hardware Friendly Classifiers Through Algorithmic Risk Minimization. Advances in Neural Networks 2016: 403-413 - 2015
- [j9]Luca Oneto, Alessandro Ghio, Sandro Ridella, Davide Anguita:
Learning Resource-Aware Classifiers for Mobile Devices: From Regularization to Energy Efficiency. Neurocomputing 169: 225-235 (2015) - [j8]Luca Oneto, Alessandro Ghio, Sandro Ridella, Davide Anguita:
Local Rademacher Complexity: Sharper risk bounds with and without unlabeled samples. Neural Networks 65: 115-125 (2015) - [j7]Luca Oneto, Alessandro Ghio, Sandro Ridella, Davide Anguita:
Fully Empirical and Data-Dependent Stability-Based Bounds. IEEE Trans. Cybern. 45(9): 1913-1926 (2015) - [c32]Luca Oneto, Ilenia Orlandi, Davide Anguita:
Performance assessment and uncertainty quantification of predictive models for smart manufacturing systems. IEEE BigData 2015: 1436-1445 - [c31]Mehrnoosh Vahdat, Luca Oneto, Davide Anguita, Mathias Funk, Matthias Rauterberg:
A Learning Analytics Approach to Correlate the Academic Achievements of Students with Interaction Data from an Educational Simulator. EC-TEL 2015: 352-366 - [c30]Luca Oneto, Bernardo Pilarz, Alessandro Ghio, Davide Anguita:
Model Selection for Big Data: Algorithmic Stability and Bag of Little Bootstraps on GPUs. ESANN 2015 - [c29]Mehrnoosh Vahdat, Alessandro Ghio, Luca Oneto, Davide Anguita, Mathias Funk, Matthias Rauterberg:
Advances in learning analytics and educational data mining. ESANN 2015 - [c28]Mehrnoosh Vahdat, Luca Oneto, Alessandro Ghio, Davide Anguita, Mathias Funk, Matthias Rauterberg:
Human Algorithmic Stability and Human Rademacher Complexity. ESANN 2015 - [c27]Luca Oneto, Alessandro Ghio, Sandro Ridella, Davide Anguita:
Shrinkage learning to improve SVM with hints. IJCNN 2015: 1-9 - [c26]Luca Oneto, Alessandro Ghio, Sandro Ridella, Davide Anguita:
Support vector machines and strictly positive definite kernel: The regularization hyperparameter is more important than the kernel hyperparameters. IJCNN 2015: 1-4 - [c25]Luca Oneto, Alessandro Ghio, Sandro Ridella, Davide Anguita:
Fast convergence of extended Rademacher Complexity bounds. IJCNN 2015: 1-10 - [c24]Jorge Luis Reyes-Ortiz, Luca Oneto, Davide Anguita:
Big Data Analytics in the Cloud: Spark on Hadoop vs MPI/OpenMP on Beowulf. INNS Conference on Big Data 2015: 121-130 - [c23]Emanuele Fumeo, Luca Oneto, Davide Anguita:
Condition Based Maintenance in Railway Transportation Systems Based on Big Data Streaming Analysis. INNS Conference on Big Data 2015: 437-446 - [d4]Jorge Luis Reyes-Ortiz, Davide Anguita, Luca Oneto, Xavier Parra:
Smartphone-Based Recognition of Human Activities and Postural Transitions. UCI Machine Learning Repository, 2015
- [d3]Mehrnoosh Vahdat, Luca Oneto, Davide Anguita, Mathias Funk, Matthias Rauterberg:
Educational Process Mining (EPM): A Learning Analytics Data Set. UCI Machine Learning Repository, 2015 - 2014
- [j6]Davide Anguita, Alessandro Ghio, Luca Oneto, Sandro Ridella:
Unlabeled patterns to tighten Rademacher complexity error bounds for kernel classifiers. Pattern Recognit. Lett. 37: 210-219 (2014) - [j5]Davide Anguita, Alessandro Ghio, Luca Oneto, Sandro Ridella:
A Deep Connection Between the Vapnik-Chervonenkis Entropy and the Rademacher Complexity. IEEE Trans. Neural Networks Learn. Syst. 25(12): 2202-2211 (2014) - [c22]Mehrnoosh Vahdat, Luca Oneto, Alessandro Ghio, Giuliano Donzellini, Davide Anguita, Mathias Funk, Matthias Rauterberg:
A Learning Analytics Methodology to Profile Students Behavior and Explore Interactions with a Digital Electronics Simulator. EC-TEL 2014: 596-597 - [c21]Davide Anguita, Alessandro Ghio, Luca Oneto, Sandro Ridella:
Learning with few bits on small-scale devices: From regularization to energy efficiency. ESANN 2014 - [c20]Alessandro Ghio, Luca Oneto:
Byte The Bullet: Learning on Real-World Computing Architectures. ESANN 2014 - [c19]Jorge Luis Reyes-Ortiz, Luca Oneto, Alessandro Ghio, Albert Samà, Davide Anguita, Xavier Parra:
Human Activity Recognition on Smartphones with Awareness of Basic Activities and Postural Transitions. ICANN 2014: 177-184 - [c18]Luca Oneto, Alessandro Ghio, Sandro Ridella, Jorge Luis Reyes-Ortiz, Davide Anguita:
Out-of-Sample Error Estimation: The Blessing of High Dimensionality. ICDM Workshops 2014: 637-644 - [c17]Davide Anguita, Alessandro Ghio, Luca Oneto, Sandro Ridella:
Smartphone battery saving by bit-based hypothesis spaces and local Rademacher Complexities. IJCNN 2014: 3916-3921 - [d2]Andrea Coraddu, Luca Oneto, Alessandro Ghio, Stefano Savio, Davide Anguita, Massimo Figari:
Condition Based Maintenance of Naval Propulsion Plants. UCI Machine Learning Repository, 2014 - 2013
- [j4]Davide Anguita, Alessandro Ghio, Luca Oneto, Xavier Parra, Jorge Luis Reyes-Ortiz:
Energy Efficient Smartphone-Based Activity Recognition using Fixed-Point Arithmetic. J. Univers. Comput. Sci. 19(9): 1295-1314 (2013) - [j3]Luca Oneto, Alessandro Ghio, Davide Anguita, Sandro Ridella:
An improved analysis of the Rademacher data-dependent bound using its self bounding property. Neural Networks 44: 107-111 (2013) - [c16]Davide Anguita, Alessandro Ghio, Luca Oneto, Xavier Parra, Jorge Luis Reyes-Ortiz:
A Public Domain Dataset for Human Activity Recognition using Smartphones. ESANN 2013 - [c15]Davide Anguita, Alessandro Ghio, Luca Oneto, Sandro Ridella:
A Learning Machine with a Bit-Based Hypothesis Space. ESANN 2013 - [c14]Davide Anguita, Alessandro Ghio, Luca Oneto, Xavier Parra, Jorge Luis Reyes-Ortiz:
Training Computationally Efficient Smartphone-Based Human Activity Recognition Models. ICANN 2013: 426-433 - [c13]Davide Anguita, Alessandro Ghio, Luca Oneto, Jorge Luis Reyes-Ortiz, Sandro Ridella:
A Novel Procedure for Training L1-L2 Support Vector Machine Classifiers. ICANN 2013: 434-441 - [c12]Davide Anguita, Alessandro Ghio, Luca Oneto, Sandro Ridella:
Some results about the Vapnik-Chervonenkis entropy and the rademacher complexity. IJCNN 2013: 1-8 - [c11]Davide Anguita, Alessandro Ghio, Luca Oneto, Sandro Ridella:
A support vector machine classifier from a bit-constrained, sparse and localized hypothesis space. IJCNN 2013: 1-10 - 2012
- [j2]Davide Anguita, Alessandro Ghio, Luca Oneto, Sandro Ridella:
In-sample Model Selection for Trimmed Hinge Loss Support Vector Machine. Neural Process. Lett. 36(3): 275-283 (2012) - [j1]Davide Anguita, Alessandro Ghio, Luca Oneto, Sandro Ridella:
In-Sample and Out-of-Sample Model Selection and Error Estimation for Support Vector Machines. IEEE Trans. Neural Networks Learn. Syst. 23(9): 1390-1406 (2012) - [c10]Davide Anguita, Luca Ghelardoni, Alessandro Ghio, Luca Oneto, Sandro Ridella:
The 'K' in K-fold Cross Validation. ESANN 2012 - [c9]Davide Anguita, Alessandro Ghio, Luca Oneto, Sandro Ridella:
Structural Risk Minimization and Rademacher Complexity for Regression. ESANN 2012 - [c8]Alessandro Ghio, Davide Anguita, Luca Oneto, Sandro Ridella, Carlotta Schatten:
Nested Sequential Minimal Optimization for Support Vector Machines. ICANN (2) 2012: 156-163 - [c7]Luca Oneto, Davide Anguita, Alessandro Ghio, Sandro Ridella:
Rademacher Complexity and Structural Risk Minimization: An Application to Human Gene Expression Datasets. ICANN (2) 2012: 491-498 - [c6]Davide Anguita, Alessandro Ghio, Luca Oneto, Xavier Parra, Jorge Luis Reyes-Ortiz:
Human Activity Recognition on Smartphones Using a Multiclass Hardware-Friendly Support Vector Machine. IWAAL 2012: 216-223 - [d1]Jorge Luis Reyes-Ortiz, Davide Anguita, Alessandro Ghio, Luca Oneto, Xavier Parra:
Human Activity Recognition Using Smartphones. UCI Machine Learning Repository, 2012 - 2011
- [c5]Davide Anguita, Alessandro Ghio, Luca Oneto, Sandro Ridella:
Maximal Discrepancy vs. Rademacher Complexity for error estimation. ESANN 2011 - [c4]Davide Anguita, Alessandro Ghio, Luca Oneto, Sandro Ridella:
In-sample model selection for Support Vector Machines. IJCNN 2011: 1154-1161 - [c3]Davide Anguita, Alessandro Ghio, Luca Oneto, Sandro Ridella:
Selecting the hypothesis space for improving the generalization ability of Support Vector Machines. IJCNN 2011: 1169-1176 - [c2]Luca Oneto, Davide Anguita, Alessandro Ghio, Sandro Ridella:
The Impact of Unlabeled Patterns in Rademacher Complexity Theory for Kernel Classifiers. NIPS 2011: 585-593 - 2010
- [c1]Davide Anguita, Alessandro Ghio, Noemi Greco, Luca Oneto, Sandro Ridella:
Model selection for support vector machines: Advantages and disadvantages of the Machine Learning Theory. IJCNN 2010: 1-8
Coauthor Index
[j62] [j61] [i8] [b1] [j58] [c104] [c102] [c101] [c99] [j55] [j53] [j50] [c95] [c94] [c93] [c92] [c89] [j44] [c87] [c85] [c83] [c81] [c80] [j41] [j39] [c76] [e2] [e1] [j35] [j32] [c63] [c62] [c61] [c60] [c59] [c55] [c54] [j30] [j28] [j27] [j26] [j25] [j24] [c52] [c51] [c50] [c48] [j22] [j21] [j20] [j19] [j18] [c45] [c44] [c43] [c42] [c41] [c40] [j17] [j16] [j15] [j14] [j13] [j12] [j11] [j10] [c39] [c38] [c37] [c36] [c35] [c34] [c33] [p1] [j9] [j8] [j7] [c32] [c31] [c30] [c29] [c28] [c27] [c26] [c25] [c24] [c23] [d4] [d3] [j6] [j5] [c22] [c21] [c19] [c18] [c17] [d2] [j4] [j3] [c16] [c15] [c14] [c13] [c12] [c11] [j2] [j1] [c10] [c9] [c8] [c7] [c6] [d1] [c5] [c4] [c3] [c2] [c1]
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