| A public domain dataset for human activity recognition using smartphones. D Anguita, A Ghio, L Oneto, X Parra, JL Reyes-Ortiz Esann 3, 3, 2013 | 2711 | 2013 |
| Human activity recognition on smartphones using a multiclass hardware-friendly support vector machine D Anguita, A Ghio, L Oneto, X Parra, JL Reyes-Ortiz Ambient Assisted Living and Home Care: 4th International Workshop, IWAAL …, 2012 | 1259 | 2012 |
| Transition-aware human activity recognition using smartphones JL Reyes-Ortiz, L Oneto, A Samā, X Parra, D Anguita Neurocomputing 171, 754-767, 2016 | 801 | 2016 |
| Empirical risk minimization under fairness constraints M Donini, L Oneto, S Ben-David, JS Shawe-Taylor, M Pontil Advances in neural information processing systems 31, 2018 | 516 | 2018 |
| The'K'in K-fold Cross Validation. D Anguita, L Ghelardoni, A Ghio, L Oneto, S Ridella ESANN 102, 441-446, 2012 | 470 | 2012 |
| Technical analysis and sentiment embeddings for market trend prediction A Picasso, S Merello, Y Ma, L Oneto, E Cambria Expert Systems with Applications 135, 60-70, 2019 | 295 | 2019 |
| Big data analytics in the cloud: Spark on hadoop vs mpi/openmp on beowulf JL Reyes-Ortiz, L Oneto, D Anguita Procedia Computer Science 53, 121-130, 2015 | 274 | 2015 |
| Energy efficient smartphone-based activity recognition using fixed-point arithmetic D Anguita, A Ghio, L Oneto, FX Llanas Parra, JL Reyes Ortiz Journal of universal computer science 19 (9), 1295-1314, 2013 | 253 | 2013 |
| Data-driven ship digital twin for estimating the speed loss caused by the marine fouling A Coraddu, L Oneto, F Baldi, F Cipollini, M Atlar, S Savio Ocean Engineering 186, 106063, 2019 | 235 | 2019 |
| Machine learning approaches for improving condition-based maintenance of naval propulsion plants A Coraddu, L Oneto, A Ghio, S Savio, D Anguita, M Figari Proceedings of the Institution of Mechanical Engineers, Part M: Journal of …, 2016 | 215 | 2016 |
| Vessels fuel consumption forecast and trim optimisation: A data analytics perspective A Coraddu, L Oneto, F Baldi, D Anguita Ocean Engineering 130, 351-370, 2017 | 199 | 2017 |
| Condition based maintenance in railway transportation systems based on big data streaming analysis E Fumeo, L Oneto, D Anguita Procedia Computer Science 53, 437-446, 2015 | 191 | 2015 |
| Fairness in machine learning L Oneto, S Chiappa Recent trends in learning from data: Tutorials from the inns big data and …, 2020 | 153 | 2020 |
| In-sample and out-of-sample model selection and error estimation for support vector machines D Anguita, A Ghio, L Oneto, S Ridella IEEE Transactions on Neural Networks and Learning Systems 23 (9), 1390-1406, 2012 | 143 | 2012 |
| Train delay prediction systems: a big data analytics perspective L Oneto, E Fumeo, G Clerico, R Canepa, F Papa, C Dambra, N Mazzino, ... Big data research 11, 54-64, 2018 | 132 | 2018 |
| Model selection for support vector machines: Advantages and disadvantages of the machine learning theory D Anguita, A Ghio, N Greco, L Oneto, S Ridella The 2010 international joint conference on neural networks (IJCNN), 1-8, 2010 | 132 | 2010 |
| Statistical learning theory and ELM for big social data analysis L Oneto, F Bisio, E Cambria, D Anguita ieee CompUTATionAl inTelliGenCe mAGAzine 11 (3), 45-55, 2016 | 122 | 2016 |
| Fair regression with wasserstein barycenters E Chzhen, C Denis, M Hebiri, L Oneto, M Pontil Advances in Neural Information Processing Systems 33, 7321-7331, 2020 | 115 | 2020 |
| Leveraging labeled and unlabeled data for consistent fair binary classification E Chzhen, C Denis, M Hebiri, L Oneto, M Pontil Advances in Neural Information Processing Systems 32, 2019 | 107 | 2019 |
| Dynamic delay predictions for large-scale railway networks: Deep and shallow extreme learning machines tuned via thresholdout L Oneto, E Fumeo, G Clerico, R Canepa, F Papa, C Dambra, N Mazzino, ... IEEE Transactions on Systems, Man, and Cybernetics: Systems 47 (10), 2754-2767, 2017 | 103 | 2017 |
Davide AnguitaDIBRIS - University of Genova, ItalyVerifierad e-postadress på unige.it
