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

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Jennifer Leger,Esther Bollhöfermapping based graph regulated NMF (EFM GNMF), which combines ELM feature mapping with Graph Regularized Nonnegative Matrix Factorization (GNMF). Experiments on the COIL20 image library, the CMU PIE face database and TDT2 corpus show the efficiency of the proposed method.

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https://doi.org/10.1007/978-3-8350-9488-8elections by using K-nearest neighbor (KNN) algorithm. A series of experiments and comparisons with other five methods were implemented to validate the feasibility and superiority of this technique for improving the positioning accuracy.

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Efficient Data Representation Combining with ELM and GNMF,mapping based graph regulated NMF (EFM GNMF), which combines ELM feature mapping with Graph Regularized Nonnegative Matrix Factorization (GNMF). Experiments on the COIL20 image library, the CMU PIE face database and TDT2 corpus show the efficiency of the proposed method.

filial

,An Improved Weight Optimization and Cholesky Decomposition Based Regularized Extreme Learning Machihe experiments of COW-RELM algorithm have been conducted on the Breast, Leukemia, Colon, Heart and other gene expression data. The results are thus presented to show the excellent performance and effectiveness of the classification accuracy.