Cantitate/Preț
Produs
Total produse
Vezi coșul
Proceedings of ELM-2015 Volume 1: Theory, Algorithms and Applications (I) de Jiuwen Cao

Proceedings of ELM-2015 Volume 1: Theory, Algorithms and Applications (I): Proceedings in Adaptation, Learning and Optimization, cartea 6

Editat de Jiuwen Cao, Kezhi Mao, Jonathan Wu, Amaury Lendasse
en Limba Engleză Hardback – 25 ian 2016
This book contains some selected papersfrom the International Conference on Extreme Learning Machine 2015,which was held in Hangzhou, China,December 15-17,2015.This conference brought together researchers and engineers to share andexchange R&D experience on both theoretical studies and practicalapplications of the Extreme Learning Machine (ELM) technique and brainlearning.
This book covers theories, algorithms adapplications of ELM. It gives readers a glance of the most recent advances ofELM. 
Citește tot Restrânge

Toate formatele și edițiile

Toate formatele și edițiile Preț Express
Paperback (1) 123512 lei  6-8 săpt.
  Springer International Publishing – 30 mar 2018 123512 lei  6-8 săpt.
Hardback (1) 124145 lei  6-8 săpt.
  Springer International Publishing – 25 ian 2016 124145 lei  6-8 săpt.

Din seria Proceedings in Adaptation, Learning and Optimization

Preț: 124145 lei

Preț vechi: 155181 lei
-20% Nou

Puncte Express: 1862
Preț estimativ în valută:
23760€ • 25065$ • 19800£

Carte tipărită la comandă

Livrare economică 02-16 ianuarie 25

 Adaugă în coș

Wish list
Gift list
Am citit!
Adaugă în listă
Preluare comenzi: 021 569.72.76

Specificații

ISBN-13: 9783319283968
ISBN-10: 3319283960
Pagini: 532
Ilustrații: IX, 532 p. 213 illus., 93 illus. in color.
Dimensiuni: 155 x 235 x 30 mm
Greutate: 0.93 kg
Ediția:1st ed. 2016
Editura: Springer International Publishing
Colecția Springer
Seria Proceedings in Adaptation, Learning and Optimization

Locul publicării:Cham, Switzerland

Public țintă

Research

Cuprins

Efficient BatchParallel Online Sequential Extreme Learning Machine Algorithm Based on MapReduce.- Fixed-PointEvaluation of Extreme LearningMachine for Classification.- Multi-Layer OnlineSequential Extreme Learning Machine for Image Classification.- ELM Meets UrbanComputing: Ensemble Urban Data For Smart City Applications.- Local and GlobalUnsupervised Kernel Extreme Learning Machine and Its Application in NonlinearProcess Fault Detection.- Parallel Multi-GraphClassification Using Extreme Learning Machine and MapReduce.- Extreme LearningMachine for Large-Scale Graph Classification Based on MapReduce.- The Distance-basedRepresentative Skyline Calculation using Unsupervised Extreme  Learning Machines.-  Multi-label Text Categorization Using L21-NormMinimizationExtreme Learning Machine.- Cluster-based Outlier Detection Using Unsupervised Extreme Learning Machines.- Segmentation of the LeftVentriclein Cardiac MRI Using an ELM Model.- Channel EstimationBased on Extreme Learning Machine for High Speed Environments.- MIMO Modeling Basedon Extreme Learning Machine.- Graph Classificationbased on Sparse Graph Feature Selection and Extreme Learning Machine.- Time SeriesPrediction Based on Online Sequential Improved Error Minimized Extreme Learning Machine.- Adaptive Input Shaping for Flexible Systemsusing an Extreme Learning Machine Algorithm Identification.- Kernel BasedSemi-supervised Extreme Learning Machine and the Application in TrafficCongestion Evaluation.- Improvement of ELMAlgorithm for Multi-Object Identification in Gesture Interaction.- SVM and ELM: WhoWins? Object Recognition withDeep Convolutional Features from ImageNet.- Learning withSimilarity Functions: a Novel Design for the Extreme Learning Machine.- A Semi-SupervisedLow Rank Kernel Learning Algorithm via Extreme Learning Machine.- Application ofExtreme Learning Machine on Large Scale Traffic Congestion Prediction.- Extreme LearningMachine-Guided Collaborative Coding for Remote Sensing Image Classification.- Distributed WeightedExtreme Learning Machine for Big Imbalanced Data Learning.- NMR ImageSegmentation based on Unsupervised Extreme Learning Machine.- Annotating LocationSemantic Tags in LBSN Using Extreme Learning Machine.- Feature Extractionof Motor Imagery EEG based on Extreme Learning Machine Auto-Encoder.- Multimodal Fusionusing Kernel-based ELM for Video Emotion Recognition.- EqualityConstrained-Optimization-Based Semi-Supervised ELM for Modeling.- Signal Strength Temporal Variation in Indoor LocationEstimation Extreme LearningMachine with Gaussian Kernel Based Relevance Feedback Scheme for Image Retrieval.- Routing TreeMaintenance based on Trajectory Prediction in Mobile Sensor Networks.- Two-Stage HybridExtreme Learning Machine for Sequential Imbalanced Data.- Feature Selectionand Modelling of a Steam Turbine from a Combined Heat and Power Plant Using ELM.- On The Constructionof Extreme Learning Machine for One Class Classifier.- Record Linkage forEvent Identification in XML Feeds Stream Using ELM.- Timeliness OnlineRegularized Extreme Learning Machine.- An EfficientHigh-dimensional Big Data Storage Structure Based on US-ELM.- An Enhanced Extreme Learning Machine for Efficient Small SampleClassification.- Code Generation Technology of Digital Satellite.- ELM-based Velocity Inversion for Sandstone Reservoir in YanqiGas-Field.- Class-Constrained Extreme Learning Machine.
 
 

Textul de pe ultima copertă

This book contains some selected papersfrom the International Conference on Extreme Learning Machine 2015,which was held in Hangzhou, China,December 15-17,2015.This conference brought together researchers and engineers to share andexchange R&D experience on both theoretical studies and practicalapplications of the Extreme Learning Machine (ELM) technique and brainlearning.
This book covers theories, algorithms adapplications of ELM. It gives readers a glance of the most recent advances ofELM. 

Caracteristici

Focuses on the conference theme of Big Data Analysis, Machine Learning and Biological Learning Results of the International Conference on Extreme Learning Machines (ELM-2015) held at Hangzhou, China, December 15-17, 2015 Presents Theory, Algorithms and Applications Includes supplementary material: sn.pub/extras