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Advances in big data : proceedings of the 2nd INNS Conference on Big Data, October 23-25, 2016, Thessaloniki, Greece / Plamen Angelov, Yannis Manolopoulos, Lazaros Iliadis, Asim Roy, Marley Vellasco, editors

By: International Neural Network Society.. Conference on Big Data ((2nd : 2016 : Thessalonikē, Greece))
Contributor(s): Angelov, Plamen P.,, editor literario | Manolopoulos, Yannis, (1957-), editor literario | Roy, Asim,, editor literario | Vellasco, Marley Maria B. R.,, editor literario
Material type: materialTypeLabelE-bookSeries: (Advances in intelligent systems and computing, 2194-5357 ; 529).Publisher: Cham : Springer, [2017]Copyright date: 2017Description: 1 recurso en línea : ilustraciones (algunas a color).ISBN: 3319478982; 9783319478982.Subject: Datos masivos -- Congresos y conferenciasOnline resources: Acceso a este recurso digital (usuarios Universidad Europea de Madrid)Digital Resources
Contents:
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.
Abstract: 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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Holdings
Item type Current library Collection Call number Status Date due Barcode Item holds
LIBRO-E NO PRÉSTAMO LIBRO-E NO PRÉSTAMO Madrid Digital Acceso Electrónico (UEM) Ciencias e Ingeniería QA76.9 .B45 2017 EB (Browse shelf(Opens below)) Acceso electrónico eBook.20022355
Total holds: 0

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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.

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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