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An incremental model selection algorithm based on cross-validation for finding the architecture of a Hidden Markov model on hand gesture data sets
(IEEE, 2009-12-13)
In a multi-parameter learning problem, besides choosing the architecture of the learner, there is the problem of finding the optimal parameters to get maximum performance. When the number of parameters to be tuned increases, ...
Subset selection for tuning of hyper-parameters in artificial neural networks
(IEEE, 2017)
Hyper-parameters of a machine learning architecture define its design. Tuning of hyper-parameters is costly and for large data sets outright impractical, whether it is performed manually or algorithmically. In this study ...