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 pra...

Πίνακας περιεχομένων:

• 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.