Decomposition Techniques for Multilayer Perceptron Training
暂无分享,去创建一个
[1] S. Hyakin,et al. Neural Networks: A Comprehensive Foundation , 1994 .
[2] Chee Kheong Siew,et al. Extreme learning machine: Theory and applications , 2006, Neurocomputing.
[3] David H. Mathews,et al. Detection of non-coding RNAs on the basis of predicted secondary structure formation free energy change , 2006, BMC Bioinformatics.
[4] Marco Sciandrone,et al. A convergent decomposition method for box-constrained optimization problems , 2009, Optim. Lett..
[5] Marco Sciandrone,et al. Continuous Optimization On the convergence of inexact block coordinate descent methods for constrained optimization , 2013 .
[6] Magnus R. Hestenes,et al. Conjugate Direction Methods in Optimization , 1980 .
[7] Jorge Nocedal,et al. On the limited memory BFGS method for large scale optimization , 1989, Math. Program..
[8] Chee Kheong Siew,et al. Universal Approximation using Incremental Constructive Feedforward Networks with Random Hidden Nodes , 2006, IEEE Transactions on Neural Networks.
[9] MSc PhD Adrian J. Shepherd BA. Second-Order Methods for Neural Networks , 1997, Perspectives in Neural Computing.
[10] Yiqiang Chen,et al. Weighted extreme learning machine for imbalance learning , 2013, Neurocomputing.
[11] Jesús Alcalá-Fdez,et al. KEEL Data-Mining Software Tool: Data Set Repository, Integration of Algorithms and Experimental Analysis Framework , 2011, J. Multiple Valued Log. Soft Comput..
[12] Ed Anderson,et al. LAPACK Users' Guide , 1995 .
[13] Luigi Grippof,et al. Globally convergent block-coordinate techniques for unconstrained optimization , 1999 .
[14] Luigi Grippo,et al. Convergent Decomposition Techniques for Training RBF Neural Networks , 2001, Neural Computation.
[15] Dianhui Wang,et al. Extreme learning machines: a survey , 2011, Int. J. Mach. Learn. Cybern..
[16] S. Bonettini. Inexact block coordinate descent methods with application to non-negative matrix factorization , 2011 .
[17] Heekuck Oh,et al. Neural Networks for Pattern Recognition , 1993, Adv. Comput..
[18] Guang-Bin Huang,et al. An Insight into Extreme Learning Machines: Random Neurons, Random Features and Kernels , 2014, Cognitive Computation.
[19] P. Tseng,et al. On the convergence of the coordinate descent method for convex differentiable minimization , 1992 .
[20] Hongming Zhou,et al. Extreme Learning Machine for Regression and Multiclass Classification , 2012, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).
[21] Allan Pinkus,et al. Approximation theory of the MLP model in neural networks , 1999, Acta Numerica.
[22] Marcos Raydan,et al. The Barzilai and Borwein Gradient Method for the Large Scale Unconstrained Minimization Problem , 1997, SIAM J. Optim..
[23] John N. Tsitsiklis,et al. Parallel and distributed computation , 1989 .
[24] Yurii Nesterov,et al. Efficiency of Coordinate Descent Methods on Huge-Scale Optimization Problems , 2012, SIAM J. Optim..
[25] Chee Kheong Siew,et al. Incremental extreme learning machine with fully complex hidden nodes , 2008, Neurocomputing.
[26] Luigi Grippo,et al. Nonmonotone Globalization Techniques for the Barzilai-Borwein Gradient Method , 2002, Comput. Optim. Appl..