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Parameter Identifiability in Statistical Machine Learning: A Review 期刊论文
NEURAL COMPUTATION, 2017, 卷号: 29, 期号: 5, 页码: 1151-1203
作者:  Ran, Zhi-Yong;  Hu, Bao-Gang
Adobe PDF(466Kb)  |  收藏  |  浏览/下载:337/101  |  提交时间:2017/07/18
Parameter Identifiability  Statistical Machine Learning  
An identifying function approach for determining parameter structure of statistical learning machines 期刊论文
NEUROCOMPUTING, 2015, 卷号: 162, 页码: 209-217
作者:  Ran, Zhi-Yong;  Hu, Bao-Gang
Adobe PDF(386Kb)  |  收藏  |  浏览/下载:334/80  |  提交时间:2015/09/17
Identifying Function  Structural Identifiability  Statistical Learning Machine  Kullback-leibler Divergence  Parameter Redundancy  Reparameterization  
Determining structural identifiability of parameter learning machines 期刊论文
NEUROCOMPUTING, 2014, 卷号: 127, 期号: 1, 页码: 88-97
作者:  Ran, Zhi-Yong;  Hu, Bao-Gang
Adobe PDF(515Kb)  |  收藏  |  浏览/下载:316/79  |  提交时间:2015/08/12
Identifiability  Parameter Learning Machine  Exhaustive Summary  Kullback-leibler Divergence  Parameter Redundancy  
Determining parameter identifiability from the optimization theory framework: A Kullback-Leibler divergence approach 期刊论文
NEUROCOMPUTING, 2014, 卷号: 142, 期号: 2, 页码: 307-317
作者:  Ran, Zhi-Yong;  Hu, Bao-Gang
Adobe PDF(563Kb)  |  收藏  |  浏览/下载:278/70  |  提交时间:2015/08/12
Identifiability  Optimization Theory  Kullback-leibler Divergence  Hessian Matrix  Jacobian Matrix  
Variational learning for Generalized Associative Functional Networks in modeling dynamic process of plant growth 期刊论文
ECOLOGICAL INFORMATICS, 2009, 卷号: 4, 期号: 3, 页码: 163-176
作者:  Qu, Han-Bing;  Hu, Bao-Gang
收藏  |  浏览/下载:167/0  |  提交时间:2015/08/12
Functional Equations  Generalized Associative Functional Networks  Variational Bayes  Bayesian Backfitting  Dynamic Plant Growth Modeling