Proceedings of ELM-2015 Volume 2 (eBook, PDF)

Theory, Algorithms and Applications (II)
Redaktion: Cao, Jiuwen; Lendasse, Amaury; Wu, Jonathan; Mao, Kezhi

• Format: PDF

Produktbeschreibung

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.

---

Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.

Produktdetails

• Verlag: Springer Nature Switzerland
• Seitenzahl: 516
• Erscheinungstermin: 2. Januar 2016
• Englisch
• ISBN-13: 9783319283739
• Artikelnr.: 44485283

Inhaltsangabe

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 UsingELM.- 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 andEntorhinal 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 ExtremeLearning Machine for Regression.- WELM Extreme Learning Machine with Wavelet Dynamic Co-Movement Analysis in High-Dimensional Time Series.