Proceedings of ELM-2015 Volume 2 Theory, Algorithms and Applications (II) /

• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Άλλοι συγγραφείς: Cao, Jiuwen (Επιμελητής έκδοσης), Mao, Kezhi (Επιμελητής έκδοσης), Wu, Jonathan (Επιμελητής έκδοσης), Lendasse, Amaury (Επιμελητής έκδοσης)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2016.
• Έκδοση: 1st ed. 2016.
• Σειρά: Proceedings in Adaptation, Learning and Optimization, 7
• Θέματα: Engineering.; Data mining.; Artificial intelligence.; Bioinformatics.; Computational intelligence.; Computational Intelligence.; Artificial Intelligence (incl. Robotics).; Computational Biology/Bioinformatics.; Data Mining and Knowledge Discovery.

 This 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. . 

 Large-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：Extreme Learning Machine with Wavelet Dynamic Co-Movement Analysis in High-Dimensional Time Series.