000 | 05731nam a22005775i 4500 | ||
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001 | 978-3-319-28373-9 | ||
003 | DE-He213 | ||
005 | 20200421112555.0 | ||
007 | cr nn 008mamaa | ||
008 | 160102s2016 gw | s |||| 0|eng d | ||
020 |
_a9783319283739 _9978-3-319-28373-9 |
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024 | 7 |
_a10.1007/978-3-319-28373-9 _2doi |
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050 | 4 | _aQ342 | |
072 | 7 |
_aUYQ _2bicssc |
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072 | 7 |
_aCOM004000 _2bisacsh |
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082 | 0 | 4 |
_a006.3 _223 |
245 | 1 | 0 |
_aProceedings of ELM-2015 Volume 2 _h[electronic resource] : _bTheory, Algorithms and Applications (II) / _cedited by Jiuwen Cao, Kezhi Mao, Jonathan Wu, Amaury Lendasse. |
250 | _a1st ed. 2016. | ||
264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2016. |
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300 |
_aIX, 516 p. 146 illus., 94 illus. in color. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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338 |
_aonline resource _bcr _2rdacarrier |
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347 |
_atext file _bPDF _2rda |
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490 | 1 |
_aProceedings in Adaptation, Learning and Optimization, _x2363-6084 ; _v7 |
|
505 | 0 | _aLarge-Scale Scene Recognition based on Extreme Learning Machines -- Partially Connected ELM for Fast and Effective Scene Classification Optimization -- Two-Layer Extreme Learning Machine for Dimension Reduction -- Distributed Extreme Learning Machine with Alternating Direction Method of Multiplier -- An Adaptive Online Sequential Extreme Learning Machine for Real-Time Tidal Level Prediction -- Optimization of Outsourcing ELM problems in Cloud Computing from Multi-Parties -- H-MRST: A Novel Framework For Support Uncertain Data Range Query Using ELM -- The SVM-ELM Model based on Particle Swarm Optimization -- ELM-ML: Study on Multi-Label Classification using Extreme Learning Machine -- Sentiment Analysis of Chinese Micro Blog based on DNN and ELM and Vector Space Model -- Self Forward and Information Dissemination Prediction Research in SINA Microblog Using ELM -- Sparse Coding Extreme Learning Machine for Classification -- Continuous Top-K Remarkable comments Over Textual Streaming Data Using ELM -- ELM based Representational Learning for Fault Diagnosis of Wind Turbine Equipment -- Prediction of Pulp Concentration Using Extreme Learning Machine -- Rational and Self-Adaptive Evolutionary Extreme Learning Machine for Electricity Price Forecast -- Contractive ML-ELM for Invariance Robust Feature Extraction -- Automated Human Facial Expression Recognition Using Extreme Learning Machines -- Multi-Modal Deep Extreme Learning Machine for Robotic Grasping Recognition -- Denoising Deep Extreme Learning Machines for Sparse Representation -- Extreme Learning Machine based Point-of-Interest Recommendation in Location-based Social Networks -- The Granule-Based Interval Forecast for Wind Speed -- KELM : An Improved K-means Clustering Method using Extreme Learning Machine -- Wind Power Ramp Events Classification using Extreme Learning Machines -- Facial Expression Recognition Based on Ensemble Extreme Learning Machine with Eye Movements Information -- Correlation between Extreme Learning Machine and Entorhinal Hippocampal System -- RNA Secondary Structure Prediction using Extreme Learning Machine with Clustering Under-Sampling Technique -- Multi-Instance Multi-label learning by Extreme Learning Machine -- A Randomly Weighted Gabor Network for Visual-Thermal Infrared Face Recognition -- Dynamic Adjustment of Hidden Layer Structure for Convex Incremental Extreme Learning Machine -- ELMVIS+: Improved Nonlinear Visualization Technique using Cosine Distance and Extreme Learning Machines -- On Mutual Information over non-Euclidean Spaces, Data Mining and Data Privacy Levels -- Probabilistic Methods for Multiclass Classification Problems -- A Pruning Ensemble Model of Extreme Learning Machine with L1/2 Regularizer -- Evaluating Confidence Intervals for ELM Predictions -- Real-Time Driver Fatigue Detection Based on ELM -- A High Speed Multi-label Classifier based on Extreme Learning Machines -- Image Super-Resolution by PSOSEN of Local Receptive Fields Based Extreme Learning Machine -- Sparse Extreme Learning Machine for Regression -- WELM$1!+:(BExtreme Learning Machine with Wavelet Dynamic Co-Movement Analysis in High-Dimensional Time Series. | |
520 | _aThis book contains some selected papers from 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 and exchange R&D experience on both theoretical studies and practical applications of the Extreme Learning Machine (ELM) technique and brain learning. This book covers theories, algorithms ad applications of ELM. It gives readers a glance of the most recent advances of ELM. . | ||
650 | 0 | _aEngineering. | |
650 | 0 | _aData mining. | |
650 | 0 | _aArtificial intelligence. | |
650 | 0 | _aBioinformatics. | |
650 | 0 | _aComputational intelligence. | |
650 | 1 | 4 | _aEngineering. |
650 | 2 | 4 | _aComputational Intelligence. |
650 | 2 | 4 | _aArtificial Intelligence (incl. Robotics). |
650 | 2 | 4 | _aComputational Biology/Bioinformatics. |
650 | 2 | 4 | _aBioinformatics. |
650 | 2 | 4 | _aData Mining and Knowledge Discovery. |
700 | 1 |
_aCao, Jiuwen. _eeditor. |
|
700 | 1 |
_aMao, Kezhi. _eeditor. |
|
700 | 1 |
_aWu, Jonathan. _eeditor. |
|
700 | 1 |
_aLendasse, Amaury. _eeditor. |
|
710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer eBooks | |
776 | 0 | 8 |
_iPrinted edition: _z9783319283722 |
830 | 0 |
_aProceedings in Adaptation, Learning and Optimization, _x2363-6084 ; _v7 |
|
856 | 4 | 0 | _uhttp://dx.doi.org/10.1007/978-3-319-28373-9 |
912 | _aZDB-2-ENG | ||
942 | _cEBK | ||
999 |
_c59076 _d59076 |