Learning the pseudoinverse solution to network weights
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[1] Y. Takane,et al. Generalized Inverse Matrices , 2011 .
[2] Yann LeCun,et al. The mnist database of handwritten digits , 2005 .
[3] Teuvo Kohonen,et al. Self-organization and associative memory: 3rd edition , 1989 .
[4] T. Greville,et al. Some Applications of the Pseudoinverse of a Matrix , 1960 .
[5] Mattia Rigotti,et al. A Simple Derivation of a Bound on the Perceptron Margin Using Singular Value Decomposition , 2011, Neural Computation.
[6] Heekuck Oh,et al. Neural Networks for Pattern Recognition , 1993, Adv. Comput..
[7] Steve B. Furber,et al. Real time on-chip implementation of dynamical systems with spiking neurons , 2012, The 2012 International Joint Conference on Neural Networks (IJCNN).
[8] Kwabena Boahen,et al. Silicon Neurons That Compute , 2012, ICANN.
[9] Narasimhan Sundararajan,et al. On-Line Sequential Extreme Learning Machine , 2005, Computational Intelligence.
[10] Xiao-Jing Wang,et al. Internal Representation of Task Rules by Recurrent Dynamics: The Importance of the Diversity of Neural Responses , 2010, Front. Comput. Neurosci..
[11] C. Eliasmith,et al. Learning to Select Actions with Spiking Neurons in the Basal Ganglia , 2012, Front. Neurosci..
[12] Teuvo Kohonen,et al. Self-Organizing Maps , 2010 .
[13] Michael R. Lyu,et al. A pseudoinverse learning algorithm for feedforward neural networks with stacked generalization applications to software reliability growth data , 2004, Neurocomputing.
[14] Adi Ben-Israel,et al. Generalized inverses: theory and applications , 1974 .
[15] L. Glass,et al. Oscillation and chaos in physiological control systems. , 1977, Science.
[16] Teuvo Kohonen,et al. Self-Organization and Associative Memory , 1988 .
[17] Pavel Kovanic. On the pseudoinverse of a sum of symmetric matrices with applications to estimation , 1979, Kybernetika.
[18] Erkki Oja,et al. Neural Networks, Principal Components, and Subspaces , 1989, Int. J. Neural Syst..
[19] Teuvo Kohonen,et al. Correlation Matrix Memories , 1972, IEEE Transactions on Computers.
[20] Pat Langley,et al. Editorial: On Machine Learning , 1986, Machine Learning.
[21] Chris Eliasmith,et al. Neural Engineering: Computation, Representation, and Dynamics in Neurobiological Systems , 2004, IEEE Transactions on Neural Networks.
[22] Yoshua Bengio,et al. Gradient-based learning applied to document recognition , 1998, Proc. IEEE.
[23] Zhenghao Chen,et al. On Random Weights and Unsupervised Feature Learning , 2011, ICML.
[24] Eero P. Simoncelli,et al. Natural signal statistics and sensory gain control , 2001, Nature Neuroscience.
[25] Chris Eliasmith,et al. Fine-Tuning and the Stability of Recurrent Neural Networks , 2011, PloS one.
[26] Lawrence K. Saul,et al. Large-Margin Classification in Infinite Neural Networks , 2010, Neural Computation.
[27] R. O’Reilly. Six principles for biologically based computational models of cortical cognition , 1998, Trends in Cognitive Sciences.
[28] AI Koan. Weighted Sums of Random Kitchen Sinks : Replacing minimization with randomization in learning , 2008 .
[29] Chee Kheong Siew,et al. Extreme learning machine: Theory and applications , 2006, Neurocomputing.