Proceedings of ELM-2015. Volume 1, Theory, algorithms and applications (I)

• 作者： International Conference on Extreme Learning Machine (2015 : Hangzhou, China)
• 其他作者：
  • Cao, Jiuwen, editor.
  • Mao, Kezhi, editor.
  • Wu, Jonathan, editor.
  • Lendasse, Amaury, editor.
  • SpringerLink (Online service)
• 其他題名：
  • Theory, algorithms and applications (I)
  • Proceedings in adaptation, learning and optimization ;
• 出版： Cham : Springer International Publishing :Imprint: Springer
• 叢書名： Proceedings in adaptation, learning and optimization,volume 6
• 主題： Artificial intelligence--Congresses. , Computational intelligence--Congresses. , Engineering. , Computational Intelligence. , Artificial Intelligence (incl. Robotics) , Computational Biology/Bioinformatics. , Bioinformatics. , Data Mining and Knowledge Discovery.
• ISBN： 9783319283975 (electronic bk.) 、 9783319283968 (paper)
• FIND@SFXID: CGU
• 資料類型: 電子書
• 內容註: Efficient Batch Parallel Online Sequential Extreme Learning Machine Algorithm Based on MapReduce -- Fixed-Point Evaluation of Extreme Learning Machine for Classification -- Multi-Layer Online Sequential Extreme Learning Machine for Image Classification -- ELM Meets Urban Computing: Ensemble Urban Data For Smart City Applications -- Local and Global Unsupervised Kernel Extreme Learning Machine and Its Application in Nonlinear Process Fault Detection -- Parallel Multi-Graph Classification Using Extreme Learning Machine and MapReduce -- Extreme Learning Machine for Large-Scale Graph Classification Based on MapReduce -- The Distance-based Representative Skyline Calculation using Unsupervised Extreme Learning Machines -- Multi-label Text Categorization Using L21-NormMinimization Extreme Learning Machine -- Cluster-based Outlier Detection Using Unsupervised Extreme Learning Machines -- Segmentation of the Left Ventricle in Cardiac MRI Using an ELM Model -- Channel Estimation Based on Extreme Learning Machine for High Speed Environments -- MIMO Modeling Based on Extreme Learning Machine -- Graph Classification based on Sparse Graph Feature Selection and Extreme Learning Machine -- Time Series Prediction Based on Online Sequential Improved Error Minimized Extreme Learning Machine -- Adaptive Input Shaping for Flexible Systems using an Extreme Learning Machine Algorithm Identification -- Kernel Based Semi-supervised Extreme Learning Machine and the Application in Traffic Congestion Evaluation -- Improvement of ELM Algorithm for Multi-Object Identification in Gesture Interaction -- SVM and ELM: Who Wins? Object Recognition with Deep Convolutional Features from ImageNet -- Learning with Similarity Functions: a Novel Design for the Extreme Learning Machine -- A Semi-Supervised Low Rank Kernel Learning Algorithm via Extreme Learning Machine -- Application of Extreme Learning Machine on Large Scale Traffic Congestion Prediction -- Extreme Learning Machine-Guided Collaborative
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• 摘要註: 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.
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