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Advances in Big Data: Proceedings of the 2nd INNS Conference on Big Data, October 23-25, 2016, Thessaloniki, Greece: Advances in Intelligent Systems and Computing, cartea 529

Editat de Plamen Angelov, Yannis Manolopoulos, Lazaros Iliadis, Asim Roy, Marley Vellasco
en Limba Engleză Paperback – 9 oct 2016
The book offers a timely snapshot of neural network technologies as a significant component of big data analytics platforms. It promotes new advances and research directions in efficient and innovative algorithmic approaches to analyzing big data (e.g. deep networks, nature-inspired and brain-inspired algorithms); implementations on different computing platforms (e.g. neuromorphic, graphics processing units (GPUs), clouds, clusters); and big data analytics applications to solve real-world problems (e.g. weather prediction, transportation, energy management). The book, which reports on the second edition of the INNS Conference on Big Data, held on October 23–25, 2016, in Thessaloniki, Greece, depicts an interesting collaborative adventure of neural networks with big data and other learning technologies.
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Specificații

ISBN-13: 9783319478975
ISBN-10: 3319478974
Pagini: 365
Ilustrații: XVII, 348 p. 101 illus.
Dimensiuni: 155 x 235 x 19 mm
Greutate: 0.51 kg
Ediția:1st ed. 2017
Editura: Springer International Publishing
Colecția Springer
Seria Advances in Intelligent Systems and Computing

Locul publicării:Cham, Switzerland

Cuprins

Predicting human behavior based on web search activity: Greek referendum of 2015.- Compact Video Description and Representation for Automated Summarization of Human Activities.- Attribute Learning for Network Intrusion Detection.- A Fast Deep Convolutional Neural Network for face detection in Big Visual Data.- Learning Symbols by Neural Network.- Designing HMMs models in the age of Big Data.- Extended Formulations for Online Action Selection on Big Action Sets.- Multi-Task Deep Neural Networks for Automated Extraction of Primary Site and Laterality Information from Cancer Pathology Reports.- An infrastructure and approach for infering knowledge over Big Data in the Vehicle Insurance Industry.- Unified Retrieval Model of Big Data.- Adaptive Elitist Differential Evolution Extreme Learning Machines on Big Data: Intelligent Recognition of Invasive Species.

Textul de pe ultima copertă

The book offers a timely snapshot of neural network technologies as a significant component of big data analytics platforms. It promotes new advances and research directions in efficient and innovative algorithmic approaches to analyzing big data (e.g. deep networks, nature-inspired and brain-inspired algorithms); implementations on different computing platforms (e.g. neuromorphic, graphics processing units (GPUs), clouds, clusters); and big data analytics applications to solve real-world problems (e.g. weather prediction, transportation, energy management). The book, which reports on the second edition of the INNS Conference on Big Data, held on October 23–25, 2016, in Thessaloniki, Greece, depicts an interesting collaborative adventure of neural networks with big data and other learning technologies.



Caracteristici

Reports on the latest neural network technologies for big data analytics Presents innovative algorithmic approaches to analyzing big data Describes big data analytics applications to solve real-world problems Includes supplementary material: sn.pub/extras