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Recent Advances in Big Data and Deep Learning : Proceedings of the INNS Big Data and Deep Learning Conference INNSBDDL2019, held at Sestri Levante, Genova, Italy 16-18 April 2019 / / edited by 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 INNSBDDL2019, held at Sestri Levante, Genova, Italy 16-18 April 2019 / / edited by Luca Oneto, Nicolò Navarin, Alessandro Sperduti, Davide Anguita |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
| Descrizione fisica | 1 online resource (402 pages) |
| Disciplina |
005
005.7 |
| Collana | Proceedings of the International Neural Networks Society |
| Soggetto topico |
Engineering—Data processing
Computational intelligence Artificial intelligence Data Engineering Computational Intelligence Artificial Intelligence |
| ISBN | 3-030-16841-7 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | On the trade-off between number of examples and precision of supervision in regression -- Distributed SmSVM Ensemble Learning -- Size/Accuracy Trade-off in Convolutional Neural Networks: An Evolutionary Approach -- Fast transfer learning for image polarity detection -- Dropout for Recurrent Neural Networks -- Psychiatric disorders classification with 3D Convolutional Neural Networks -- Perturbed Proximal Descent to Escape Saddle Points for Non-convex and Non-smooth Objective Functions -- Deep-learning domain adaptation techniques for credit cards fraud detection -- Selective Information Extraction Strategies for Cancer Pathology Reports with Convolutional Neural Networks -- An information theoretic approach to the autoencoder -- Deep Regression Counting: Customized Datasets and Inter-Architecture Transfer Learning -- Improving Railway Maintenance Actions with Big Data and Distributed Ledger Technologies. |
| Record Nr. | UNINA-9910483127803321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Recent Trends in Learning From Data : Tutorials from the INNS Big Data and Deep Learning Conference (INNSBDDL2019) / / edited by Luca Oneto, Nicolò Navarin, Alessandro Sperduti, Davide Anguita
| Recent Trends in Learning From Data : Tutorials from the INNS Big Data and Deep Learning Conference (INNSBDDL2019) / / edited by Luca Oneto, Nicolò Navarin, Alessandro Sperduti, Davide Anguita |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
| Descrizione fisica | 1 online resource (vii, 221 pages) |
| Disciplina | 006.31 |
| Collana | Studies in Computational Intelligence |
| Soggetto topico |
Computational intelligence
Machine learning Engineering—Data processing Computational Intelligence Machine Learning Data Engineering |
| ISBN | 3-030-43883-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Introduction: Recent Trends in Learning From Data -- Learned data structures -- Deep Randomized Neural Networks -- Tensor Decompositions and Practical Applications -- Deep learning for graphs -- Limitations of Shallow Networks -- Fairness in Machine Learning -- Online Continual Learning on Sequences. |
| Record Nr. | UNINA-9910483445703321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||