Titlebook: Extreme Learning Machines 2013: Algorithms and Applications; Fuchen Sun,Kar-Ann Toh,Kezhi Mao Book 2014 Springer International Publishing

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1867-4534 g, to promote research and discussions of “l(fā)earning without iterative tuning"..This book covers algorithms and applications of ELM. It gives readers a glance of the newest developments of ELM..978-3-319-35003-5978-3-319-04741-6Series ISSN 1867-4534 Series E-ISSN 1867-4542

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Freshwater Algal Bloom Prediction by Extreme Learning Machine in Macau Storage Reservoirs,solid (SS) and total organic carbon (TOC) selected from the correlation analysis of the 23?monthly water variables were included, with 8?years (2001–2008) data for training and the most recent 3?years (2009–2011) for testing. The modeling results showed that the prediction and forecast (based on dat

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ELM-Based Adaptive Live Migration Approach of Virtual Machines,es a weight-based measurement method of writable working set, which can accurately measure the writable working set, so that it can reduce the amount of dirty memory page transmission, meanwhile it uses a memory compression algorithm to compress memory pages to be transmitted, and thus reduces the d

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Demographic Attributes Prediction Using Extreme Learning Machine,latively independent data from complicated original dataset. In the next step, the extracted data goes through different paths based on their types. And at the last step, all the data will be transformed into a demographic attributes matrix. To fulfill prediction, the demographic attributes matrix i

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A Novel Scene Based Robust Video Watermarking Scheme in DWT Domain Using Extreme Learning Machine,hat the proposed watermarking scheme produces best results due to optimized embedding facilitated by fast training of the ELM. The proposed scheme is found to be suitable for developing real time video watermarking applications due to its low time complexity.

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Extreme Learning Machines 2013: Algorithms and Applications

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Die Wirklichkeit des Menschen im Unternehmens sensitivity per attribute. The results show a strong consistency for classifiers with different random input weights. In order to present the results obtained in an intuitive way, two forms of representation are proposed and contrasted against each other. The relevance of both attributes and class

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Jennifer Leger,Esther Bollh?feron, data clustering etc. As the process of NMF needs huge computation cost, especially when the dimensional of data is large. Thus a ELM feature mapping based NMF is proposed [.], which combined Extreme Learning Machine (ELM) feature mapping with NMF (EFM NMF), can reduce the computational of NMF. H