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| Artikel-Nr.:
5667A-9783030438852 Herst.-Nr.:
9783030438852 EAN/GTIN:
9783030438852 |
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| This book offers a timely snapshot and extensive practical and theoretical insights into the topic of learning from data. Based on the tutorials presented at the INNS Big Data and Deep Learning Conference, INNSBDDL2019, held on April 16-18, 2019, in Sestri Levante, Italy, the respective chapters cover advanced neural networks, deep architectures, and supervised and reinforcement machine learning models. They describe important theoretical concepts, presenting in detail all the necessary mathematical formalizations, and offer essential guidance on their use in current big data research. Weitere Informationen: | | Author: | Luca Oneto; Nicolò Navarin; Alessandro Sperduti; Davide Anguita | Verlag: | Springer International Publishing | Sprache: | eng |
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| Weitere Suchbegriffe: maschinenbau und fertigungstechnik, Deep Learning for Graphs, Feedforward neural networks, Applications of tensor decomposition, Continual learning models, Learned data structures, Causal bayesian networks, Online continual learning, Deep learning models, Sparsity of shallow networks, Growing neural networks, Searching problems |
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