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2020 – today
- 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 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) - 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 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 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 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 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 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 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 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]