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2022
Data concerning the project Nature Gradient of Lise Meitner Group for Environmental ...
Sudimac, Sonja, Sztuka, Izabela Maria
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Data concerning the project Nature Gradient of Lise Meitner Group for Environmental ...
Sudimac, Sonja, Sztuka, Izabela Maria
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Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181), 2002
Gradient adaptation is a useful technique for adjusting a set of parameters to minimize a cost function. While often easy to implement, the convergence speed of gradient adaptation can be slow when the slope of the cost function varies widely for small changes in the parameters.
S. Amari, S.C. Douglas
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Gradient adaptation is a useful technique for adjusting a set of parameters to minimize a cost function. While often easy to implement, the convergence speed of gradient adaptation can be slow when the slope of the cost function varies widely for small changes in the parameters.
S. Amari, S.C. Douglas
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Gradient direction dependencies in natural images
Spatial Vision, 2007We have used information-theoretic measures to compute the amount of dependency which exists between two and three gradient directions at separate locations in an ensemble of natural images. Control experiments were performed on other image classes: phase randomized natural images, whitened natural images and Gaussian noise images.
Alexandre J, Nasrallah, Lewis D, Griffin
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Electrofocusing in natural pH gradients formed by buffers: Gradient modification
Analytical Biochemistry, 1977Abstract Natural pH gradients formed in buffers (1) can be shifted in slope or in parallel along the pH scale by addition or substitution of buffers to obtain, for each particular fractionation problem, a gradient in which the species of interest occupies the center position.
N Y, Nguyen, A, Salokangas, A, Chrambach
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Natural Gradient Learning Algorithms for RBF Networks
Neural Computation, 2015Radial basis function (RBF) networks are one of the most widely used models for function approximation and classification. There are many strange behaviors in the learning process of RBF networks, such as slow learning speed and the existence of the plateaus. The natural gradient learning method can overcome these disadvantages effectively.
Zhao, Junsheng +5 more
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Rprop Using the Natural Gradient
2005Gradient-based optimization algorithms are the standard methods for adapting the weights of neural networks. The natural gradient gives the steepest descent direction based on a non-uclidean, from a theoretical point of view more appropriate metric in the weight space. While the natural gradient has already proven to be advantageous for online learning,
Christian Igel +2 more
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Natural Conjugate Gradient Training of Multilayer Perceptrons
Neurocomputing, 2006Natural gradient (NG) descent, arguably the fastest on-line method for multilayer perceptron (MLP) training, exploits the ''natural'' Riemannian metric that the Fisher information matrix defines in the MLP weight space. It also accelerates ordinary gradient descent in a batch setting but then the Fisher matrix essentially coincides with the Gauss ...
Ana González, José R. Dorronsoro
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Computationally efficient natural gradient descent
1998DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY AND INFORMATION SERVICES WITH PRIOR ...
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Integrative oncology: Addressing the global challenges of cancer prevention and treatment
Ca-A Cancer Journal for Clinicians, 2022Jun J Mao,, Msce +2 more
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