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Accurate validation of GCV-based regularization parameter for extreme learning machine

2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI), 2017
Extreme Learning Machine (ELM) is a neural network architecture with Single Layer Feed-forward Neural Network (SLFN). For meaningful results, the structure of ELM has to be optimized through the inclusion of regularization and the l 2 — norm based regularization is mostly used.
Shraddha M. Naik, Ravi Prasad K. Jagannath +1 more
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Thresholding and GCV applicability in more realistic situations

2001
We have exploited the sparsity of a wavelet representation to motivate thresholding as a curve fitting method and to find GCV as an asymptotically optimal threshold assessment procedure. We explained that sparsity is a sort of smoothness and explained that wavelets are well suited to measure this concept of piecewise smoothness.
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CGLS-GCV: a hybrid algorithm for low-rank-deficient problems

Applied Numerical Mathematics, 2003
An algorithm is given for solving two rank-deficient problems: construction of a minimum norm solution of the unperturbed least squares problem for a linear system and computation of approximations of the column (row) space of the coefficient matrix. The algorithm's attribute is the satisfactory detection of the rank even if the singular spectrum has ...
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GCV Computation for biomass