Results 41 to 50 of about 527,249 (162)
Mathematics, 2022 The high accuracy attainment, using less complex architectures of neural networks, remains one of the most important problems in machine learning. In many studies, increasing the quality of recognition and prediction is obtained by extending neural ...
Ruslan Abdulkadirov +2 more
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Affine Calculus for Constrained Minima of the Kullback–Leibler Divergence
StatsThe non-parametric version of Amari’s dually affine Information Geometry provides a practical calculus to perform computations of interest in statistical machine learning.
Giovanni Pistone
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Ancient Living Organisms Escaping from, or Imprisoned in, the Vents?
Life, 2017 We have recently criticised the natural pH gradient hypothesis which purports to explain how the difference in pH between fluid issuing from ancient alkali vents and the more acidic Hadean ocean could have driven molecular machines that catalyse ...
J. Baz Jackson
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Improving Flat Maxima with Natural Gradient for Better Adversarial Transferability
Big Data and Cognitive ComputingDeep neural networks are vulnerable and susceptible to adversarial examples, which can induce erroneous predictions by injecting imperceptible perturbations.
Yunfei Long, Huosheng Xu
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Variable-step blind source separation method with adaptive momentum factor
Tongxin xuebao, 2017 A variable-step blind source separation algorithm based on the natural gradient with adaptive momentum factor was proposed,which could cope with the determined blind source separation in the environment of stationary and non-stationary.Function ...
Tian-qi ZHANG +3 more
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Vadose Zone Journal, 2022 Clay content in soil potentially has strong influence on soil structure and thereby controls soil physical, hydraulic, and gas transport properties. Only few studies have investigated the effect of clay content on saturated hydraulic conductivity (Ks ...
Ting Yang +5 more
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Information-Geometric Optimization with Natural Selection
Entropy, 2020 Evolutionary algorithms, inspired by natural evolution, aim to optimize difficult objective functions without computing derivatives. Here we detail the relationship between classical population genetics of quantitative traits and evolutionary ...
Jakub Otwinowski +2 more
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Enhanced gradient learning for deep neural networks
IET Image Processing, 2022 Deep neural networks have achieved great success in both computer vision and natural language processing tasks. How to improve the gradient flows is crucial in training very deep neural networks. To address this challenge, a gradient enhancement approach
Ming Yan +5 more
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Analytic gradients for natural orbital functional theory [PDF]
The Journal of Chemical Physics, 2017 The analytic energy gradients with respect to nuclear motion are derived for the natural orbital functional (NOF) theory. The resulting equations do not require resorting to linear-response theory, so the computation of NOF energy gradients is analogous to gradient calculations at the Hartree-Fock level of theory.
Ion Mitxelena, Mario Piris
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Urban-rural gradient detection using multivariate spatial analysis and landscape metrics
Journal of Agricultural Engineering, 2013 The gradient approach allows for an innovative representation of landscape composition and configuration not presupposing spatial discontinuities typical of the conventional methods of analysis.
Marco Vizzari, Maurizia Sigura
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