about
State-space analysis of time-varying higher-order spike correlation for multiple neural spike train dataConvergence analysis of evolutionary algorithms that are based on the paradigm of information geometry.Mixed signal learning by spike correlation propagation in feedback inhibitory circuits.Likelihood-based population independent component analysisPartner-matching for the automated identification of reproducible ICA components from fMRI datasets: algorithm and validation.Fast and accurate approximate inference of transcript expression from RNA-seq data.Learning maximum entropy models from finite-size data sets: A fast data-driven algorithm allows sampling from the posterior distribution.Resummed mean-field inference for strongly coupled data.Improved parameter estimation for variance-stabilizing transformation of gene-expression microarray data.Recurrent sampling models for the Helmholtz machine.The evolution of lossy compression.Image derived input function for [18F]-FEPPA: application to quantify translocator protein (18 kDa) in the human brain.A Parcellation Based Nonparametric Algorithm for Independent Component Analysis with Application to fMRI Data.Turning statistical physics models into materials design enginesCREB-BDNF pathway influences alcohol cue-elicited activation in drinkersHybrid mammogram classification using rough set and fuzzy classifier.Scalable estimation strategies based on stochastic approximations: Classical results and new insights.Parameter Identifiability in Statistical Machine Learning: A Review.Information-driven self-organization: the dynamical system approach to autonomous robot behavior.G-protein genomic association with normal variation in gray matter density.Dynamic Neural Fields with Intrinsic Plasticity.CUDAICA: GPU optimization of Infomax-ICA EEG analysisAn early underwater artificial vision model in ocean investigations via independent component analysis.Crosslinking EEG time-frequency decomposition and fMRI in error monitoring.Unsupervised neural learning on lie group.Probabilistic natural mapping of gene-level tests for genome-wide association studies.Conditional density estimation with dimensionality reduction via squared-loss conditional entropy minimization.A study on neural learning on manifold foliations: the case of the Lie group SU(3).Stiefel-manifold learning by improved rigid-body theory applied to ICA.Spike-timing error backpropagation in theta neuron networks.Dynamics of Learning in MLP: Natural Gradient and Singularity Revisited.Hebbian learning of recurrent connections: a geometrical perspective.Singularities affect dynamics of learning in neuromanifolds.Hebbian learning from higher-order correlations requires crosstalk minimization.Adaptive improved natural gradient algorithm for blind source separation.Difficulty of singularity in population coding.Learning dynamics of a single polar variable complex-valued neuron.Natural gradient learning algorithms for RBF networks.Sufficient dimension reduction via squared-loss mutual information estimation.A note on Lewicki-Sejnowski gradient for learning overcomplete representations.
P2860
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P2860
description
1998 nî lūn-bûn
@nan
1998年の論文
@ja
1998年学术文章
@wuu
1998年学术文章
@zh
1998年学术文章
@zh-cn
1998年学术文章
@zh-hans
1998年学术文章
@zh-my
1998年学术文章
@zh-sg
1998年學術文章
@yue
1998年學術文章
@zh-hant
name
Natural Gradient Works Efficiently in Learning
@en
Natural Gradient Works Efficiently in Learning
@nl
type
label
Natural Gradient Works Efficiently in Learning
@en
Natural Gradient Works Efficiently in Learning
@nl
prefLabel
Natural Gradient Works Efficiently in Learning
@en
Natural Gradient Works Efficiently in Learning
@nl
P2860
P1433
P1476
Natural Gradient Works Efficiently in Learning
@en
P2860
P304
P356
10.1162/089976698300017746
P577
1998-02-01T00:00:00Z